Methods for refining patient, staff and visitor profiles used in monitoring quality and performance at a healthcare facility

ABSTRACT

Methods, systems and computer program products are used in monitoring patients, staff, assets and visitors at a facility, initiating a response to prevent or mitigate harm, and assess and ensure overall quality and performance, and refine individual patient, staff and visitor profiles. A plurality of sensors throughout the facility provide multiple data streams relating to the locations of patients relative to at least one of caregivers, assets, other patients, visitors or one or more fixed locations. A computer system analyses the data stream and determines the location and/or movements of the patients relative to the caregivers, assets, other patients, visitors and/or fixed locations. A profile containing individual data for the patient is used to accurately detect events, including actionable events, ensure completion of prescribed care, assess patient wellness, and, in some cases, provide tailored patient specific responses to detected events. Patient profiles are periodically refined by means of an information feedback loop in order to more accurately predict (actionable) events, provide adequate care and ensure a desired level of patient wellness. Staff and visitor profiles can be used to measure staff and visitor performance at a facility.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit under 35 U.S.C. §119(e) of U.S.provisional application No. 60/748,376, filed Dec. 9, 2005, U.S.provisional application No. 60/799,041, filed May 10, 2006, U.S.provisional application No. 60/835,662, filed Aug. 4, 2006, and U.S.provisional application No. 60/826,634, filed Sep. 22, 2006. Thedisclosures of the foregoing applications are incorporated herein intheir entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention is in the field of patient monitoring systems and methodsfor assessing and ensuring a level of quality and performance providedby a healthcare facility. The invention more particularly relates toensuring that a healthcare facility is able to increase quality andperformance based on patient specific attributes and needs embodied inindividualized patient profiles, initiating appropriate responses to thepatients' needs based on such profiles, and refining the patientprofiles based on information gathered over time for each patient.

2. Relevant Technology

Healthcare facilities provide clinical and/or wellness health care forpatients and/or residents (hereinafter collectively referred to as“patients”) at such facilities. Hospitals and medical clinics provideclinical health care. Assisted living and nursing homes focus primarilyon wellness health care. Most facilities provide at least somemonitoring and supervision of patients to ensure they are receivingproper nutrition and medicines, are kept clean, and are protected fromphysical injury. A central station (e.g., a nursing station) typicallyfunctions as a primary gathering and dispatch location for caregivers.At specified intervals, or in response to a patient or resident request,a caregiver can move from the central station to a patient's location(e.g., room) and monitor or provide appropriate care.

There are often tradeoffs between ensuring that every patient at afacility receives a required level of basic care while also providingindividualized care and initiating appropriate responses based on apatient's specific behaviors, attributes and needs. Even though allpatients may receive the same basic level of care, some may receive toomuch care and others not enough care due to discrepancies between thebasic standards of care and a patient's actual needs. The result is aninefficient allocation of resources that compromises the overall qualityand performance of a facility and individual staff members.

There may be similar imbalances in interpreting patient behavior andfashioning appropriate responses. Not every patient behaves in the samemanner, has the same health problems and issues, or requiresintervention upon the occurrence of similar behaviors or events.Behavior or events that may be perfectly safe for some patients mightconstitute high risk to others. For example, an elderly person at a resthome who is ambulatory, requires no assistance to walk, and is known tosafely walk up and down stairs without falling should not triggercaregiver intervention when approaching stairs. In contrast, caregiverintervention may be appropriate when a person who is bound to a wheelchair, who can only safely walk with assistance, or who has difficultyin perceiving or evaluating danger approaches a staircase.

One specific area of concern involves unassisted bed exiting, wheelchairexiting, wheelchair to bed transfer, or other support exiting.Unassisted support exiting by invalids or the elderly is a significantcause of injury and liability. Falls often occur due to the inability ofhealth care facilities to provide continuous, direct supervision ofpatients. Unfortunately, it is typically not feasible to provide roundthe clock supervision of every patient due to financial and/orlogistical restraints. Nevertheless, without continuous directsupervision and/or a reliable system of early notification, there may beno way for a health care provider to know when a particular patient maybe engaging in support exiting or other behavior which places them athigh risk for falling.

Other measurements of quality and performance involve maintainingpatients within defined safety or security zones, tracking and analyzingpatient gait or daily ambulation to diagnose potential injury or healthissues, tracking patient contacts with assigned caregivers and/or thirdparties, monitoring patient socialization, initiating patientsurveillance upon the occurrence of a triggering event, tracking staffmovements and activities, tracking visitor movements and activities,responding to patient initiated calls or alerts, tracking assets used toprovide patient care (e.g., medical devices, walkers, dentures, etc.),verifying the occurrence of prescribed treatments for each patient, andthe like.

Notwithstanding the need to monitor and supervise patients to ensure anadequate level of quality and performance and prevent patient injury,the United States, Europe, Japan and other parts of the world arecurrently experiencing a serious shortage of nurses, nursing assistants,doctors, and other caregivers. Such shortage will only worsen withcontinued aging of the population. As the patient to caregiver ratio ata facility increases, the ability to provide adequate patient care andprotection are likely to decrease as more patients are left unattended.There is therefore an acute need for new methods and systems that canbetter safeguard patients and improve the quality and performance ofcare delivery at a facility while also reducing facility liability,enhancing caregiver productivity, and lowering operational expenses.

Although automated patient monitoring systems have been proposed, theytypically lack feasibility and have not been implemented on a widescale. The problem with conventional patient monitoring systems is theirinability to interpret and distinguish between safe or appropriatepatient behaviors or conditions and those that are potentially dangerousor inappropriate as among different patients. Standard limits and alarmlevels may be too tight or too loose depending on the patient. Theresult can be a high incidence of false positives in the case wherelimits and alarm levels are too tight and false negatives in the casewhere limits and alarm levels are too loose. A high rate of falsepositives can become like the boy crying wolf and might be ignored byoverworked caregivers. False negatives provide no early warning ofpotential patient harm.

For example, one type of patient monitoring system utilizes sensors todetect patient bed exiting. A common problem that leads to a high levelof false positives and false negatives is a “one size fits all” approachto detecting and interpreting patient movements. Although people oftenhave uniquely personal ways of getting out of bed, no attempt is made inconventional monitoring systems to understand the specific movements andhabits of a particular patient when bed exiting. For example, onepatient might typically grasp the left handrail when commencing to bedexit while another might slide towards the foot of the bed. Persons whoare left handed might exit their beds oppositely from right handedpersons. Certain medical conditions might determine or alter bed exitingbehavior (e.g., a person with a newly formed incision might protectagainst harm or pain by avoiding movements that would apply stress tothe incision, even if such movements were previously used to bed exitwhen the patient was healthy).

In view of the foregoing, it would be an advancement in the art toprovide methods and systems for monitoring patient, staff and visitoractivities that can more accurately detect and interpret individualbehaviors and conditions as they pertain to the overall quality andperformance by a facility in delivering health care to its patients.Reducing the incidence of false positives and false negatives whendetecting actionable events would be expected to increase the ability ofa healthcare facility to provide an appropriate response thereto,intervene when necessary to prevent harm to a patient, and increase theoverall quality and performance of the facility in providing for thespecific needs of a patient as among a plurality of different patients.

SUMMARY OF THE INVENTION

The present invention relates to patient monitoring methods and systemsused to ensure an appropriate level of quality provided to the patientsand performance by staff and visitors at a healthcare facility. Realtime data regarding the locations, movements and/or behaviors of each ofa plurality of patients, caregivers, visitors and assets is obtainedfrom multiple sources and analyzed by a computer system (e.g., facilitymaster). The computer system meaningfully interprets the data throughthe use of individualized patient specific profiles in order tointerpret the overall quality of service provided to each patient at ahealthcare facility. In addition, the individual performance by staffand visitors, as they relate to the overall performance of the facility,can be evaluated through the use of staff and visitor specific profiles.When a patient, staff or visitor specific limit is approached orbreeched, the computer system may initiate an appropriate response toprevent or mitigate patient harm, unauthorized access to restrictedzones, or other inappropriate or harmful actions.

Data regarding the location, movements and/or behaviors of patients,staff, visitors and assets throughout or outside a facility can begathered using any detection means known in the art including, but notlimited to, RFID devices, an RFID detection grid, GPS devices, cameras,motion detectors, light beam detectors, image analysis systems and thelike. In-room surveillance cameras can be used to generate a data streamthat is interpreted by a local computer system (e.g., in roomcontroller), such as to detect movements or behaviors that may lead tounassisted support exiting by a patient. Motion and light beam detectorsmay also be used to detect patient, staff or visitor movements andgenerate data that can be analyzed by the computer system.

When a limit or alarm level is reached, a video feed from a surveillancecamera may be sent to a nursing station for verification or denial bystaff that a triggering event actually occurred and that a response isrequired to prevent or mitigate patient harm or prevent inappropriateactivity. The verification or denial by staff forms an informationfeedback loop that can be used to refine patient, staff or visitorprofiles to tighten or loosen limits or alarm levels as appropriate tomore accurately identify the occurrence of triggering events in thefuture. Profiles can also be updated to reflect the occurrence ofnon-occurrence of prescribed activities, as may be automaticallydetermined by tracking the locations of patients, staff, assets andvisitors at a facility. The refinement of profiles over time allows thesystem to “learn” and store individualized data regarding the specificbehaviors, attributes and performance of patients, staff or visitors atthe facility. This reduces the instances of false positives and falsenegatives as it relates to detecting triggering events.

Examples of quality and performance criteria (e.g., care and wellness)include, but are not limited to, ensuring the general safety of patients(e.g., preventing and/or intervening in the case of unassisted supportexiting, maintaining patients within prescribed geographic zones withinor without a facility, responding to patient emergencies or alerts, andthe like), assessing the status of prescribed actions (e.g., whichinvolve caregivers, assets, patient-initiated behaviors, and the like),and assessing the status of patient's general health and well being(e.g., patient nutrition, ambulation tracking, denture use, use ofwalking aids, socialization, privacy, pain level, rollovers to preventbed sores, and the like).

Many quality, performance, care and wellness parameters can be measuredby tracking the location of each patient relative to the locations ofcaregivers, other patients, visitors, assets and/or fixed objects orlocations. Certain care regimens or activities involve interactionsbetween patients and assigned caregivers and/or assets at specifiedlocations, often for specific durations or time intervals. Other aspectsof quality and performance involve the movement of patients betweencertain specified locations throughout a facility, often at defined timeperiods. Yet others may involve interactions between multiple patientsand/or patients and visitors. Individualized care and wellnessparameters can be established, verified and refined through the use ofspecific patient profiles, sometimes in conjunction with staff and/orvisitor profiles. By refining patient specific profiles based ongathered data relating to the specific behaviors and needs of eachpatient, the inventive systems and methods are able to interpretbehaviors, conditions and events in a highly individualized manner asamong different patients at a healthcare facility. Appropriate alarms,limits and prescriptions may be set for each patient as appropriatebased on data contained in the patient specific profiles.

A typical patient profile includes both static and dynamic data relatingto a plurality of specific care and wellness parameters. These mayinclude, for example, limits or alarm levels relating to one or more ofsupport exiting behavior and occurrence, patient ambulation, the use ofambulation devices, patient gait behavior, sound of patient breathing,dietary restrictions, prescribed levels of caregiver assistance for oneor more activities, trips to cafeteria, assisted and/or unassisted bedturning, social interactions, prescribed patient care regimens, in-roomtherapy, required therapeutic devices, denture use and cleaning,bathroom time duration, facility access or movement privileges, facilityexiting privileges, flight risk level, facility restricted areas,emergency call button usage, pet therapy contact, patient treatment bymovement of, e.g., facility assets and/or personnel, critical medicalhistory, and/or emergency contact information.

When a patient first enters a facility, a general patient profile ofcommon or known patient specific behaviors may be utilized beforespecific information is learned about the patient through theinformation feedback loop. As the profile is periodically refined basedon verified and/or rejected patient behaviors relative to a specificrisk or activity, it becomes more accurately predictive of actual riskor behavior by the patient. That reduces the incidence of falsepositives and false negatives and allows for earlier intervention intothe risk sequence. According to one embodiment, patient profiles havinginitially coarse granularity due to the lack of known patient behaviorsand attributes may have increasingly fine granularity as the profilesare refined over time. Increasing profile granularity may account foridiosyncratic movements or behaviors that are entirely unique to aparticular patient in addition to the commonly observed movements orbehaviors common to many patients.

Profile data can be uploaded to networked or peripheral computers asneeded to carry out a desired patient monitoring activity. Aninformation feedback loop can be used to update each patient profile,which may occur automatically or manually as directed by patient and/orstaff actions, in order to create and maintain a current database ofpatient status, attributes and needs. Actions that might be used torefine patient specific profile data include, for example, patientmovements that precede support exiting, changes in patient gait, socialinteractions, recursive events, patient wandering or flight, use ofemergency call button, sound of patient breathing, patient eatinghabits, observations by caregivers regarding patient behavior orcondition, and patient treatment by movement of, e.g., facility assetsand/or personnel. Information may be gathered for analysis by thecomputer system by means of RFID devices carried by patients, staff,assets, and visitors, RFID detection grids, still shot cameras, videocameras, audio recording devices, GPS devices, etc.

In the case where a triggering event is detected and verified, an alertfor direct physical intervention may be sent to a staff member assignedto a particular patient or who is close to the patient and not otherwiseoccupied. The alert may be sent to a personal data assistant carried byeach caregiver. The alerted staff member can send verification thatintervention was successful. The RFID device carried by the respondercan also be tracked automatically to verify that intervention hasoccurred. Examples of triggering events include preventing unassistedsupport exiting, preventing patient wandering into unauthorized zones,preventing patient flight from the facility, and preventing patientabuse by caregivers, other patients or visitors.

An example of using a patient specific profile to improve patientwellness involves detecting and then preventing or mitigating potentialharm caused by unassisted patient support exiting. The inventive methodsand systems can be used to monitor a patient resting on a bed (e.g.,standard hospital bed with side rails), wheelchair, gurney, couch,chair, or recliner, to which the patient may be confined and detectmovements or behaviors that are predictive of support exiting.Monitoring may be performed by one or more cameras, motion sensors,small zone RFID, and/or light beam detectors. A computer system analyzesa data stream and detects movements or behaviors that are predictive ofsupport exiting. The use of patient specific profiles helps the computersystem distinguish between movements that are predictive of supportexiting and movements that are not.

If behavior predictive of support exiting by a patient is detected, anappropriate response is triggered, examples of which include one or moreof alerting staff, establishing two-way audio-video communicationbetween staff and the patient, sending prerecorded audio and/or videowarnings to the patient's room, direct intervention by a staff member,and automated functions, such as bed lowering, raising a bedrail,turning on a light, or actuation of a patient restraint device. Similaralgorithms involving analysis of video data streams can be used todetect other movements by a patient such as patient rollover (e.g., toprevent skin damage), movements indicative of disease, movementsconsistent with prescribed behaviors, and the like.

An information feedback loop provided by a system of cameras andmonitors permits human inspection and verification of patient supportexiting before initiating audio, visual and/or physical intervention. Avideo feed of the patient is sent to a monitor at a central station(e.g., nursing station) subsequent to a visual and/or aural alert toboth the nursing station and the patient's room. A staff member viewsthe live video stream from the patient's room to determine if thepatient is actually attempting to exit the support. If so, verificationis provided to the computer system by the staff member and appropriateintervention to prevent or assist support exiting is initiated. If not,rejection is provided to the computer system. If no response to thealert is given within a prescribe time period, an automated response maybe initiated, such as sending a pre-recorded message or warning to thepatient and/or alerting nearby staff for direct physical intervention.

The information feedback loop can also be used to update a patientprofile to better predict future support exiting. The action ofverifying or rejecting an automated support exiting alert based onactual patient movements and behavior can be recorded by the computersystem and used to refine the patient profile (e.g., tightening orloosening limits) in order to better predict future support existing.The information feedback loop can also be used to refine other limits ordata in the patient profile. For example, if the monitoring systemdetects patient movements that may be indicative of flight from thefacility, wandering into unauthorized zones, or substantial changes inpatient gait, an alert may be triggered and a video feed of the patientsent to a central nurse's station. Two-way communication can also beestablished to determine the patient's actual intentions or needs. Basedon actual patient behavior, limits can be tightened or loosened tobetter predict patient flight risk, wandering, or health issues relatingto gait.

In the case where a video data stream is generated by a surveillancecamera, such as to detect support exiting or other high risk patientbehavior, it is typically deleted on an ongoing basis to protect patientprivacy. If the video stream is made available for viewing (e.g., bybeing sent to a nursing station), an alert is sent to the patient tonotify of potential third party viewing to protect privacy (e.g., bymeans of a chime, recording, visual display of words, etc.). In somecases, the video data stream may be optionally archived (e.g., recordedon a non-volatile recording medium) for later viewing and analysis of anevent. The archived video can be used to assess the overall quality andperformance of a healthcare facility. Events that might trigger videoarchiving include entry into the patient's room or personal space bystaff, visitors or other patients, manual alerts or distress signalssent by a patient, detection of other dangerous conditions (e.g.,alterations of vital signs), and requested archiving by visitingrelatives, friends, doctors or other health care providers.

The location of patients can be continuously tracked by means of anassigned RFID device worn or carried by each patient that emits a signalthat can be detected and traced to a specific location by an RFID sensorgrid. The RFID device may include an alert device that can be activatedin case of emergency of other urgent need. Because the RFID device alsoprovides means for locating the patient, assistance can be providedquickly even if the patient cannot communicate. Two-way audio-visualcommunication may be initiated via a camera, video monitor, microphoneand speaker. The alerting system may access the patient's profile inorder to tailor the response to specific patient needs. Patient usage ofthe alert feature can be tracked, analyzed and used to update thepatient's profile. For example, a patient profile may include datarelating to proper and/or improper usage of the patient alert button.

In summary, computer controlled methods and systems can be used formonitoring the location and/or activities of patients, staff, assets andvisitors and as they relate to prescribed care and wellness, respondingto actionable events, verifying wellness events, maintaining andupdating patient, staff and visitor profiles, preventing or mitigatingpatient injury, locating and assisting patients in need of assistance,and monitoring and archiving video information relating to potentiallydangerous activities.

These and other advantages and features of the present invention willbecome more fully apparent from the following description and appendedclaims, or may be learned by the practice of the invention as set forthhereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the invention can be obtained, a moreparticular description of the invention briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered to be limiting of its scope, the invention will bedescribed and explained with additional specificity and detail throughthe use of the accompanying drawings, in which:

FIG. 1 schematically illustrates various exemplary computer-clientnetwork protocols that can be used to facilitate communication between afacility master computer system and peripheral clients;

FIG. 2 schematically illustrates an exemplary facility monitoring mastersystem;

FIG. 3 schematically illustrates exemplary computer architecture thatfacilitates facility, patient, staff and/or asset monitoring and eventresponse management;

FIG. 4 is a flow chart that illustrates an exemplary method for managinga response to an actionable event in a healthcare facility;

FIG. 5 is a flow chart that illustrates an exemplary method formaintaining alarm levels in a patient risk profile for a patient of ahealthcare facility;

FIG. 6 is a flow chart that illustrates an exemplary method fordetermining patient care and wellness using individualized patientprofiles;

FIG. 7 schematically illustrates the interrelationship of various datagathering and analysis modules used to maintain and refine a patientprofile;

FIG. 8 is a flow chart that illustrates an exemplary method formaintaining stored profiles for a plurality of patients at a healthcarefacility;

FIG. 9 schematically illustrates an exemplary system for patientmonitoring, alert and response;

FIGS. 10A and 10B schematically illustrate exemplary configurations ofpatient rooms at a healthcare facility equipped for patient monitoringand response to support exiting;

FIG. 11A and 11B schematically illustrate alternative patient supportexiting detection systems;

FIG. 12 is a flow chart that illustrates an exemplary method formonitoring a patient on a support, detecting possible support exiting,and initiating a response to prevent or mitigate patient harm;

FIGS. 13A-13E schematically depict a patient in various exemplarypositions on a bed relative to known bed exiting behaviors;

FIG. 14 is a flow chart that illustrates an exemplary method forgenerating and updating a patient profile that contains data relating tosupport exiting behavior of that patient;

FIG. 15 is a flow chart that illustrates an exemplary method forresponding to a computer predicted support exiting event;

FIG. 16 is a decision chart that illustrates an exemplary decisionsequence for responding to an alert of predicted bed exiting;

FIG. 17 is a flow chart that illustrates an exemplary method forproviding an automated response to a patient initiated alert; and

FIG. 18 is a flow chart that illustrates an exemplary method forselective archiving of a video data stream of a patient in response to atriggering event.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

I. Introduction

Embodiments of the present invention extend to methods, systems, andcomputer program products for managing quality of care and performanceby staff and visitors at a healthcare facility. The invention moreparticularly relates to computer-controlled methods and systems formonitoring a plurality of patients, staff, assets and visitors at thefacility using electronic devices, computers, patient profiles, staffprofiles, visitor profiles, algorithms, human verification of triggeringevents, and direct human intervention to provide improved quality ofcare and performance based on each patient's general and individualizedneeds.

Patient specific data can be collected for each patient to create adatabase of generalized and personalized knowledge. Healthcarefacilities and providers can use the database of knowledge to betterunderstand risks associated with various activities for each patientand/or for each type of activity. Predictive modeling and artificialintelligence can be applied to collected data patterns to identify,process, categorize, alarm, and rectify risks based on patientinformation, such as, for example, patient type, patient activity,patient medications, patient physical therapy process, patient location,and other variables.

The quality and performance monitoring systems and methods of theinvention assist caregivers at a facility in ensuring and verifying thateach patient at the facility receives a prescribed level of care andalso helps ensure wellness for each of a plurality of patients based onone or more predetermined wellness criteria. To be sure, there aregeneral aspects and levels of patient care and wellness that may besubstantially similar for some or all patients, including the need foradequate rest, nutrition, cleanliness, safety, privacy, and the like. Onthe other hand, some or all patients may require specialized care andhave different wellness criteria based on individual patient needs(e.g., based on age, physical capacity, mental capacity, and the like).

The quality and performance systems and methods of the invention monitorcare and wellness for each patient by means of automated tracking ofpatients, caregivers and assets used to deliver care, and visitors. Theinventive methods and systems track patient location, activities,condition, and regimen completion, as well as assigned caregiver andasset location, activities and regimen completion. Care and wellness aremeasured in relation to individual patient profiles which are maintainedand periodically refined for each patient. The quality and performanceof staff and visitors can also be monitored and assessed using staff andvisitor profiles. According to one embodiment, the methods and systeminitiate responses to pre-determined triggering events to prevent ormitigate patient harm.

The methods and systems are implemented using a computer-controlledelectronic patient monitoring system that receives and analyzes datagenerated by a network of electronic data generating devices. A profilemaintenance and refinement sub-system and method is used to periodicallyupdate and refine patient, staff and visitor profiles as data isreceived and analyzed for individual patients, staff and visitors. Thecare and wellness of a patient, as well as the performance of staff andvisitors, can be analyzed and improved through the use of individuallyrefined profiles.

The term “patient profile” shall refer to stored data that is associatedwith a specific patient at a health facility. Patient profiles typicallyinclude static data and dynamic data. Dynamic data refers to limits andalarms that are continuously or periodically updated or refined based oninformation learned about the patient and/or changing patient needs orrequirements. Dynamic data can be automatically updated in response toevents or it may be manually updated by staff after an event.

The terms “care” and “wellness” shall be broadly understood to coverevery aspect of a patient's life and well being that are relevant tocare and treatment at a health facility. Care more particularly relatesto treatments, activities and regimens that are provided to the patientin order to ensure a prescribed or minimum level of general health andwell-being. Wellness is a measure of the general health and well-beingof the patient. Care and wellness affect the overall quality andperformance of a healthcare facility.

The term “patient fall” shall be broadly understood to include fallingto the ground or floor, falling into stationary or moving objects,falling back onto a support, or any other falling motion caused at leastin part by gravity that may potentially cause physical injury and/ormental or emotional trauma.

The terms “rest” and “resting” as it relates to a patient resting on asupport shall be broadly understood as any situation where the supportprovides at least some counter action to the force of gravity. Thus, apatient may “rest” on a support while lying still, sitting up, moving,lying down, or otherwise positioned relative to the support so long asthe support acts in some way to separate a patient from the floor orsurface upon which the support is itself positioned.

The terms “continuous monitoring” and “continuous video data stream”include taking a series of images that may be spaced apart by anyappropriate time interval so long as the time interval is sufficientlyshort that the system is not unduly hampered from initiating a responsein time to prevent or mitigate a potentially dangerous event.

The terms “receiving” and “inputting” in the context of a patientprofile broadly includes any action by which a complete or partialpatient profile, or any component thereof, is stored or entered into acomputer system. This includes, but is not limited to, creating aprofile and then storing or entering it into a computer, entering datawhich is used by the computer to generate a new patient profile, and/orstoring or entering data used by a computer for updating a pre-existingpatient profile already in the computer.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem and electronic device configurations, including, personalcomputers, desktop computers, laptop computers, hand-held devices,multi-processor systems, microprocessor-based or programmable consumerelectronics, network PCs, minicomputers, mainframe computers, mobiletelephones, PDAs, one-way and two-way pagers, Radio FrequencyIdentification (“RFID”) devices (e.g., bracelets, tags, etc.), globalposition (“GPS”) devices, and the like. The invention may also bepracticed in distributed system environments where local and remotecomputer systems, which are linked (either by hardwired data links,wireless data links, or by a combination of hardwired and wireless datalinks) through a network, both perform tasks. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

Embodiments of the present invention may comprise or utilize a specialpurpose or general-purpose computer including computer hardware, asdiscussed in greater detail below. Embodiments within the scope of thepresent invention also include physical and other computer-readablemedia for carrying or having computer-executable instructions or datastructures stored thereon. Such computer-readable media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer. By way of example, and not limitation, physicalcomputer-readable media can comprise computer-readable storage media,such as, RAM, ROM, EEPROM, CD-ROM or other optical disk storage,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store desired program code means in the formof computer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer.

A “network” is defined as one or more data links that enable thetransport of electronic data between computer systems and/or modulesand/or other electronic devices. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as acomputer-readable medium. Thus, by way of example, and not limitation,computer-readable media can comprise a network or data links which canbe used to carry or store desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. The computer executable instructions may be, forexample, binaries, intermediate format instructions such as assemblylanguage, or even source code. Although the subject matter has beendescribed in language specific to structural features and/ormethodological acts, it is to be understood that the subject matterdefined in the appended claims is not necessarily limited to thedescribed features or acts described above. Rather, the describedfeatures and acts are disclosed as example forms of implementing theclaims.

II. Computer-Implemented Electronic Patient Monitoring System and Methodfor Measuring and Verifying Quality and Performance

A. Exemplary System Architecture

According to one currently preferred embodiment, the quality andperformance monitoring systems and methods of the inventions areimplemented by means of a computer system. The computer system mayinclude one or more centralized computers, referred to as a “facilitymaster”, and one or more localized computers, exemplified by one or more“in room controllers”. The various computers within the overall computersystem divide up the task of receiving and analyzing data gathered fromthe overall patient monitoring system. FIG. 1 schematically illustratesthe relationship between various components of an exemplary computerizedsystem that can assist in monitoring the location, behavior andattributes of a plurality of patients, staff, assets and visitors at ahealthcare facility.

As seen in FIG. 1, a facility master computer system 101 receives dataregarding patients, staff, visitors and assets from a variety of datacollection clients 102 within and outside a facility. These include, forexample, in room controller clients 102 a, room associated clients 102b, support exiting monitoring clients 102 c, care giver system clients102 d, facility patient, staff, visitor and asset tracking and locationclients 102 e, external facility patient, staff and asset trackingclients 102 f, facility audio/visual clients 102 g, external facilityaudio/visual clients 102 h, and nursing station clients 102 i. The datagathered or generated by the data collection clients 102 is sent to thefacility master computer system 101 by means of communication pathways103 for analysis, response, and report. In some cases, a localizedcomputer, such as an in room controller client and/or nursing stationclient 102 i, may perform its own analysis of gathered data in order tocompartmentalize or bifurcate the tasks provided by the variouscomputers of the computer system in order to more efficiently use thecomputer system resources and reduce bottle necks.

The communication pathways 103 used to communicate gathered data fromclients 102 to facility master computer 101 are exemplified by satellite103 a, paging network 103 b, PLC/BPL 103 c, infrared network 103 d,cable/telephone network 103 e, cellular/PCS/UWB system 103 f, IEEE802.xx wireless 103 g (e.g., Wi-Fi, Wi-Max, Zigbee, etc.), RFID/GPS 103h, wireless and wired broadback internet 103 i, and public/private framerelay network 103 j (e.g., MPLS). According to one embodiment, data fromfacility master computer 101 can be periodically archived and/oranalyzed at a backup facility monitoring master system 104 (e.g., vianetwork 105).

FIG. 2 schematically illustrates an exemplary facility master computersystem 200 that can be used to control and implement quality andperformance monitoring systems and methods according to the invention.Communications interface and protocol converter 201 can receivecommunications in accordance with one of the various protocols of FIG. 1and can convert the communication so as to be compatible with aprocessing system 202. Storage 203 can store data used and produced bythe processing system 202, examples of which include archivedaudio/video data 204 a (e.g., archived in response to detection of anactionable event), profile data 204 b (e.g., patient, staff and visitordata), and algorithms 204 c used to process data and initiateappropriate responses and reports. Memory 205 can be used to buffer andquickly access short term data used or generated by the processingsystem 201.

The facility master computer system 200 includes exemplary systemcomponents 206, which are modules or applications that process datagathered by data collection and processing devices (e.g., clients 102 ofFIG. 1). Some of these modules or applications can also be run, at leastin part, by local computers, such as in room controller clients (notshown). These include audio/video management 206 a, in room clientmanagement 206 b, care giver systems management 206 c, facilitypersonnel location management 206 d, facility asset tracking andlocation management 206 e, external facility asset and personneltracking management 206 f, external facility audio/video management 206g, patient care interface and protocol management 206 h, system securitymanager 206 i, report generator manager 206 j, remote applicationinterface 206 k, data modeling subsystem 206 l, alarm manager/generator206 m, and asset management subsystem 206 n.

FIG. 3 illustrates an exemplary computer-implement monitoring system 300that monitors patients, staff, assets and visitors, assesses quality andperformance, and manages event responses at a healthcare facility.Monitoring system 300 includes a networked computer system 301, which iscomposed of a main computer system 301 a (e.g., facility master) locatedin a data center 302, first peripheral computer system 301 b (e.g., inroom controller client) at patient location 303, and second peripheralcomputer system 301 c at a central station (e.g., nurse's station). Theuse of an in room controller computer to analyze data regarding apatient within a patient room is more particularly illustrated in FIGS.10A and 10B, which are discussed more fully below. Each computer system301 a-c can be connected to a network, such as, for example, a LocalArea Network (“LAN”), a Wide Area Network (“WAN”), or even the Internet.The various components can receive and send data to each other, as wellas other components connected to the network. Networked computer systemsconstitute a “computer system” for purposes of this disclosure.

Networks facilitating communication between computer systems and otherelectronic devices can utilize any of a wide range of (potentiallyinteroperating) protocols including, but not limited to, the IEEE 802suite of wireless protocols, Radio Frequency Identification (“RFID”)protocols, infrared protocols, cellular protocols, one-way and two-waywireless paging protocols, Global Positioning System (“GPS”) protocols,wired and wireless broadband protocols, ultra-wideband “mesh” protocols,etc. Accordingly, computer systems and other devices can create messagerelated data and exchange message related data (e.g., Internet Protocol(“IP”) datagrams and other higher layer protocols that utilize IPdatagrams, such as, Transmission Control Protocol (“TCP”), RemoteDesktop Protocol (“RDP”), Hypertext Transfer Protocol (“HTTP”), SimpleMail Transfer Protocol (“SMTP”), etc.) over the network.

In some embodiments, a multi-platform, multi-network, multi-protocol,wireless and wired network architecture is utilized to monitor patient,staff, visitor, and asset locations and movements within a facility.Computer systems and electronic devices may be configured to utilizeprotocols that are appropriate based on corresponding computer systemand electronic device on functionality. For example, an electronicdevice that is to send small amounts of data a short distance within apatient's room can be configured to use Infrared protocols. On the otherhand, a computer system configured to transmit and receive largedatabase records can be configured to use an 802.11 protocol. Componentswithin the architecture can be configured to convert between variousprotocols to facilitate compatible communication. Computer systems andelectronic devices may be configured with multiple protocols and usedifferent protocols to implement different functionality. For example,an in room controller or other computer system 301 b at patient location303 can receive patient data via infrared from a biometric monitor andthen forward the patient data via fast Ethernet to computer system 301 aat data center 302 for processing.

Computer system 301 c can be physically located at a central station 304of a healthcare facility, e.g., a nursing station. Provider 305 (a nurseor other healthcare worker) can be physically located near computersystem 301 c such that provider 305 can access electronic communications(e.g., alarm 320, video feeds, A/V communications) presented at computersystem 301 c. Acknowledgment 321 can be sent to other computer systems301 a, 301 b as appropriate to verify that alarm 320 was considered byprovider 305. Other healthcare providers, such as providers 306 and 307,can be physically located in other parts of a healthcare facility.Healthcare providers can move between different locations (e.g., centralstation 304, patient rooms, hallways, outside the building, etc.).Accordingly, healthcare providers 306, 307 can also carry mobilecomputer systems (e.g., laptop computers or PDAs 308 and 309) and othertypes of mobile devices, (e.g., pagers, mobile phones, GPS devices, orRFID devices). As providers 306, 307 move about a healthcare facilitythey can still access electronic messages (e.g., alarms) and sendmessages.

Computer system 301 b, storage device 310, sensors 312, and I/O devices313 can be physically located at patient location 303, such as patientrooms, common areas, hallways, and other appropriate locationsthroughout or outside a healthcare facility. For example, patientlocation 303 can be a room of a patient 314. Sensors 312 can includevarious types of sensors, such as, for example, video cameras, stillcameras, microphones, motion sensors, pain scale sensors, pressuresensors, acoustic sensors, temperature sensors, heart rate monitors,conductivity sensors, RFID detectors, global positioning sensors(“GPS”), manual assistance switches/buttons, bed sensors, handrailsensors, mattress sensors, location sensors, oxygen tank sensors,support location sensors, call buttons, etc. Although depictedseparately, I/O devices 313 can also be sensors. Sensors and I/O devicescan also send data to any appropriate computer system for processing andevent detection, including either or both of computer systems 301 a and301 c.

Some sensors 312 can be stationary (e.g., mounted at patient location303) such that the sensors sense patient, staff, asset or visitorcharacteristics when within a specified vicinity of the sensor 312. Forexample, characteristics of a patient's gait can be observed when thepatient walks by a video camera or closely spaced apart locationsensors. A patient's gait can be monitored by measuring the time ittakes a patient to move between localized points or zones. Other sensorscan be mobile and move with a patient, provider, asset or visitor asthey move about a healthcare facility. For example, a heart rate monitorcan be attached to a patient and move with the patient to continuouslymonitor the patient's heart rate. As a patient, provider, asset orvisitor moves about a healthcare facility, different combinations ofstationary and mobile sensors can monitor the patient, provider, assetor visitor at different locations and/or times.

Each of sensors 312 can provide input to computer system 301 b. Eventdetection module 316 can monitor and process inputs from sensors 312 todetect if a combination of inputs indicates the occurrence of apotentially actionable event 317. Detecting the occurrence of event 317can trigger the transfer of various electronic messages from computersystem 301 b to other networked computers of the monitoring system 300.For example, electronic messages (alarm messages 320 regarding event317) can be transferred to computer system 301 c and/or mobile devicesto alert health care providers of an actionable event 317. Alternativelyor in addition, electronic messages including patient data 322 can betransferred to other computer systems, such as computer system 301 a,that process the patient data 322 (e.g., for refining patient profiles324 stored in storage 326). Alarm levels 325 can be sent to computersystem 301 b for use in determining whether an event 317 is actionable.

One or more of sensors 312 can be used to detect patient conditions orperformance, such as support exiting, ambulation, changes in gait,social interaction, breathing, etc. RFID zones separated by specifieddistances can be used to measure total ambulation distances and monitorspeed or interruptions in speed as a patient walks. Image analysis candetermine the manner of a patient's walk and/or support exiting.Computer system 301 b can buffer sensor input at storage device 310 forsome amount of time before discarding the input (e.g., video data). Inresponse to detecting the occurrence of an event 317, computer system301 b can locally archive sensor input or data from I/O devices 908 atstorage device 310 (e.g., A/V data 328). Buffered and/or archived sensorinput can provide the basis for patient data 322 that is transferred toother computer systems.

Event occurrences can be detected in accordance with a risk profileassociated with a monitored patient. Patient profiles 324, eitheraccessed directly from computer system 301 a or stored locally instorage 310, can be used to analyze data from sensors 312.Alternatively, alarm levels 325 can be used independently of a patientprofile 324 by local computer system 301 b. Based on differing patientprofiles 324 and/or alarm levels 325 for a plurality of patients, acombination of inputs detected as the occurrence of an (actionable)event 317 for one patient is not necessarily detected as the occurrenceof an (actionable) event 317 for another patient, and vice versa. Anactionable event can be detected when a specified alarm level for agiven patient is satisfied. For example, a specified combination of riskbehaviors and/or vital signs can cause an actionable event to bedetected.

Computer system 301 a and storage device 326 can be physically locatedat data center 302. Storage device 326 can store profiles (e.g.,profiles 324 a and 324 b) for patients, staff and visitors. Profilemanager 330 can receive patient data 322 sent to computer system 301 a(e.g., in response to a detected event) and refine a correspondingpatient profile 324 in accordance with the patient data 322. As datarelated to a patient 314 changes, the patient's profile 324 can bemodified to indicate changed risks, limits and alarm levels for thepatient 314. Risk profiles for a patient can be iteratively refined aspatient data 322 for the patient 314 is received. Algorithms forrefining profiles can be recursed on a per iteration basis.

Patients, providers, visitors and assets may carry RFID transmittingdevices, which are examples of a sensor 312, each having a uniquesignature such that an RFID transmitting device can be used to determinethe location of a patient, provider, visitor or asset within ahealthcare facility. RFID transmitting devices can be non-removable,such as a bracelet or an adhesively attached pad, or removable, such asan employee badge.

B. Event Response

Appropriate responses to an alert or alarm of an event can be providedthrough communication among and between computer systems. The differencebetween an alert and alarm is one of severity. If a trigger is minimallyexceeded, an alert is activated. Typical alert responses includenotification of event to the nursing station, establishment of A/Vcontact with patient, sounding of a tone, or verbally dispatching staffto investigate the situation. Significantly exceeding trigger value orignored alerts will generate alarms, which typically activate anautomatic PDA dispatching of staff, A/V contact and report generation.

FIG. 4 illustrates a flow chart of a method 400 for managing a responseto an actionable event in a healthcare facility. Method 400 will bedescribed with respect to the components and data in monitoring system300 of FIG. 3. Method 400 includes an act 401 of accessing input fromsensors monitoring a patient in accordance with a patient risk profile324. Further discussion regarding patient profiles is set forth later.

Method 400 further includes an act 402 of detecting the occurrence of apatient related event. For example, event detection module 316 candetect the occurrence of event 317 for patient 314 (from the input ofone or more of sensors 312). Thereafter, an act 403 involves determiningwhether the detected event is an actionable event based on a patientrisk profile 324 and/or alarm level 325. Profile manager 330 can createalarm levels 325 which are sent to event detection module 316 ofcomputer system 301 b. Alarm levels 325 can include one or morecombinations of values for inputs from sensors 312 that indicate anactionable event based on profile 324. When one or more monitored valuessatisfy an alarm level 325, an actionable event is detected.

Method 400 includes an act 404 of sending an alarm to an appropriatehealthcare provider. For example, computer system 301 b can send analarm 320, including event 317, to computer system 301 c to communicatethe occurrence of event 317 to healthcare provider 305. Thereafter, act406 involves receiving an alarm indicating an actionable event hasoccurred for the patient. For example, computer system 301 c can receivealarm 320 indicating that event 317 (an actionable event) has occurredfor patient 314 in accordance with profile 324 and/or alarm level 325.

Method 400 includes an act 407 of initiating a pre-determined responsefor assisting in the resolution of the actionable event. For example,computer system 301 c can initiate a pre-determined response forassisting in resolution of event 317 in response to receiving alarm 320.A response can include notifying an appropriate health care provider306, 307 of the occurrence of the actionable event 317. For example, inresponse to receiving alarm 320, computer system 301 c can present anaudio and/or video indication of event 317 at central station 304, suchas by means of a video display and speakers. Alternately, or inaddition, one or more of PDAs 308, 309 can receive alarm 320 and presentan audio and/or video indication of event 317 to providers either orboth of providers 306, 307.

Initiating a response 407 can include acknowledging the alarm. Forexample, computer system 301 c can send acknowledgment 321 to either orboth of computer systems 301 a, 301 b. Sending acknowledgment 321 mayresult in establishing one or two-way communication between a healthcareprovider and patient location 303 (e.g., using I/O devices 313). Forexample, provider 305 can input commands at computer system 301 c toopen communication from central station 304 to patient location 303.Similarly, providers 306, 307 can input commands at PDA's 308, 309 toopen communication from their locations to patient location 303.Communication can be used to send instructions to a patient, ascertainwhether a patient is coherent, responsive to commands or instructions,etc.

A response 407 can also include a provider responding to the location ofa patient. For example, in response to detecting that patient 314 hasfallen, might fall, or otherwise requires assistance (e.g., by a patientcontrolled call device), provider 306 or 307 can respond to patientlocation 303. RFID detectors at patient location 303 can detect an RFIDtransmitting device corresponding to provider 306 or 307 to verifyresponse by provider 306 or 307 to a patient in need (e.g., comprisingact 405 of method 400).

Expiration of a time interval can trigger some actionable events. Forexample, movement of bed bound patients to prevent bed sores oradministration of medicine can be required at specified intervals.Computer system 301 b can send an alert to computer system 301 c (orother appropriate computer systems) when a time interval expires or isabout to expire.

C. Refining Patient Risk Profiles and Modifying Alarm Levels

In some embodiments, stored patient profiles include risk profiles thatinclude recursively refined patient alarms levels indicative ofactionable events requiring a response. FIG. 5 is a flow chart thatillustrates a computerized method 500 for maintaining and refiningpatient risk profiles and associated alarms levels for a patient at ahealthcare facility. Method 500 will be described with respect to thecomponents and data in monitoring system 300. Method 500 includes an act501 of receiving collected patient data 322 related to a detected event317 for a patient 314. For example, computer system 301 a can receivepatient data 322 related to event 317 for patient 314.

As previously described, event 317 can be detected in accordance with arecursively refined risk profile 324 based on previously collectedpatient data for patient 314 (or on historical default data). Patientdata 322 is collected from a plurality of sensors 312 monitoring thepatient 314 for various conditions that, when combined or consideredindividually, indicate occurrence of an event 317. Although event 317may be an actionable event, embodiments of the invention can alsoreceive data in response to non-actionable events 317. For example, someevents 317 may trigger refinement of a patient risk profile 324 withouttriggering an alarm 320.

Method 500 includes an act 502 of refining the patient risk profile 324based on the collected patient data 322. For example, profile manager330 can refine patient risk profile 324 based on patient data 322.Profile manager 330 can adjust events 317 that are designated asactionable events for patient 314. Profile manager 330 can iterativelyrefine profile 324 through recursive application of profile refinementalgorithms.

Act 503 involves modifying alarm levels 325 for the patient 314 based onthe further refined patient risk profile 324 such that an appropriatehealth care response can be provided for alarms indicative of actionableevents. For example, profile manager 330 can adjust alarm levels 325 forpatient 314 based on refinements resulting from patient data 322. Alarmlevels 325 can cause an appropriate healthcare provider to be notifiedwhen actionable events related to patient 314 occur. Modified alarmlevels can differ from previous alarm levels for patient 314 as a resultof refinements to profile 324 to adjust risk. In some embodiments, aninformation feedback loop can be used to periodically or continuallyupdate patient profiles to fine tune the monitoring of patientconditions. For example, monitoring for bed exiting can begin withcommon preset values that are updated over time to create unique orverified information for each patient.

A decision algorithm can be used to adjust parameter values that willcause an actionable event. If an actionable event is appropriatelydetected (a positive), parameters can be made more restrictive such thatthe standard is lowered for detecting the actionable event in thefuture. For example, if a patient has fallen when exiting a bed, thevalues for detecting a bed exit can be made more restrictive. On theother hand, if an actionable event is inappropriately detected (a falsepositive), parameters can be made less restrictive such that thestandard is raised for causing or detecting the actionable event in thefuture. When no actionable event is detected (a negative) for some timeperiod, the parameters can also be made less restrictive such that thestandard is raised for causing or detecting the actionable event in thefuture.

D. Measuring Care and Wellness

Patient care and wellness can be monitored in a variety of ways.According to one embodiment, appropriate care and wellness according tocertain parameters can be determined by monitoring the locations and/ormovement of patients relative to one or more of caregivers, assets,visitors, other patients or fixed locations.

FIG. 6 is a flow chart illustrating an exemplary method 600 fordetermining patient care and wellness. Method 600 includes an act 601 ofaccessing stored patient profiles, which contain data that relate to oneor more care or wellness parameters. In most cases, the profile datawill differ as between at least some of the patients based on thespecific attributes and needs of each patient, which are rarelyidentical for all patients.

Act 602 involves identifying one or more care or wellness parameters foreach of a plurality of patients based on profile data contained in acorresponding patient profile. Examples of care or wellness parametersinclude, but are not limited to, preventing unassisted bed exiting,measuring total ambulation of a patient in a given time period,assessing the level of patient socialization with others, detectingchanges in patient gait, verifying the completion of treatments,exercises or care regimes, ensuring proper denture use, identifyingperiodic bed rolling for bed bound patients to prevent bed sores,responding to patient initiating emergency calls, preventing ormitigating patient harm, wandering or flight, ensuring proper nutrition,detecting breathing sounds, coughs, choking, etc. that may be indicativeof impaired respiratory function, ensuring that patient ambulationoccurs in association with prescribed assistive devices, and the like.

Act 603 includes determining one or more predetermined locations foreach of a plurality of patients relative to one or more predeterminedlocations for at least one of a caregiver, asset, visitor, other patientor fixed location within or without the facility which are consistentwith or that confirm or verify the satisfaction of the one or more careor wellness parameters identified in 602. Many care and wellnessparameters involve interactions between a patient and a caregiver,visitor, other patient or asset. Tracking location can also includedetermining a time duration at a location or between multiple locations.Tracking the locations of each roughly indicates whether suchinteractions have actually occurred as prescribed. A patient who isnever in the same location as the assigned individual or asset isunlikely to have had the required interaction for a care or wellnessparameter to have occurred. Tracking nutrition or preventing patientwandering or flight typically involves comparing patient movements(i.e., changing locations) relative to a fixed location in or out of afacility (e.g., cafeteria, security zone, exit, parking lot, etc.).

By way of example, patients, staff, assets and visitors can be assignedan RFID device that can be tracked throughout a facility by means of anRFID detection system comprising a plurality of RFID detectorsthroughout the facility. The location of the RFID detectors andassignment of RFID devices can be recorded and maintained in a computersystem. As patients, staff, assets and visitors move throughout thefacility, the RFID detectors notify the computer system of RFID devicesthat are currently being detected. This computer system can correlatethe location of each RFID device, as well as the duration of each RFIDdevice at a specific location, and determine whether prescribed care andwellness routines or activities involving patients, staff, assets and/orvisitors have been properly carried out.

In act 605 and 606, the actual locations of the patient, caregiver,asset, visitor, other patients and/or fixed location are compared withthe one or more predetermined locations relating to the one or more careor wellness parameters selected in 602 to determine if such care orwellness parameters have been satisfied. The location, movement and/orduration of a patient, caregiver, visitor, or other patient can bemonitored to determine if prescribed duties or activities are actuallycarried out as prescribed (e.g., performed within predetermined timeguidelines or in a proper location, such as bathing, assisted feeding,turning of bed ridden patients to prevent bed sores, etc.).

Measures can be taken to enhance patient care or wellness and/or preventor mitigate harm to a patient. Thus, act 607 includes optionallyinitiating a response to prevent or mitigate harm in the case of anactual event, refining a patient profile and/or generating a care orwellness report. By way of example, staff can be alerted to prevent ormitigate patient wandering into unauthorized or forbidden areas (e.g.,other patient rooms, facility exit, sensitive staff or equipmentlocations, etc.). Patient wellness events (e.g., social interactions,use of dentures, and proper nutrition) can be chronicled and, ifnecessary, improved through remedial action. Modification of patientprofiles can assist in more accurately predicting patient's needs andlimits. Generating a care and wellness report can assist providers orfamily members in ensuring enhanced care and wellness of the patient.

III. Profile Maintenance and Refinement

An important aspect of the inventive monitoring systems and methods forassessing and ensuring quality and performance is the use and refinementof patient specific profiles. Individual profiles permit the inventivepatient monitoring systems and methods to more accurately assess thequality of care and wellness of each patient, as among a plurality ofpatients having a variety of different attributes and needs. Staff andvisitor profiles permit analysis of staff and visitor performance at ahealthcare facility. Patient, staff and visitor profiles also permit theinventive systems and methods to better interpret conditions and actionsof patients, staff and visitors that may lead to an actionable ortriggering event. This reduces the incidence of false positives andfalse negatives and may reduce staff response times to critical clinicalevents.

FIG. 7 schematically illustrates an exemplary computer system 700containing networked computers and interrelated functional modules andperipheral data gathering systems for gathering information regarding aplurality of patients, staff and visitors at a healthcare facility andupdating patient, staff and visitor profiles. Computer system 700 moreparticularly includes a facility master 702 and in room controller 704.Of course, computer system 700 may include multiple in room controllers704 and/or other computers as desired. An RFID system interfacesdirectly with facility master 702 to provide data regarding the locationand movements of patients, staff, assets and visitors. An image analysissystem 707 interfaces directly with in room controller 704 to providedata regarding the location, behavior and/or condition of a patient in aroom. A detailed discussion regarding detecting and responding tosupport exiting is set forth below.

The exemplary modules within facility master 702 include denture tracker708, RFID zone security 710, contact tracker 712, ambulation tracker714, emergency response 716, socialization 718, surveillance controller720, mobile call button 722, and exterior GPS integration 724. The inroom controller 704 includes support exit module 726, which interpretsdata from the image analysis system 707. It will be appreciated thatadditional modules and data generating peripherals may be included asrequired to generate and process other data types. The data that isprocessed by the foregoing modules shown in FIG. 7 is used to update orrefine patient profiles 730, staff profiles 732, and visitor profiles734. Each of the data processing modules as well as exemplaryinformation contained within patient profiles 730, staff profiles 732and visitor profiles 734 will now be discussed in detail.

The following discussion of functional modules regarding profilemaintenance and refinement is also useful in understanding how theinventive methods and systems can be used to monitor and ensure adesired delivery of care and maintenance of patient wellness. They alsoassist in assessing the overall quality and performance of and at ahealthcare facility. Thus, the following discussion of functionalmodules is also applicable to understanding how the methods and systemhelp to monitor, deliver and/or ensure patient care and wellness as wellas overall quality and performance.

A. Functional Modules

1. Support Exiting Module

As discussed above, the support exiting module 726 is typically locatedwithin the in room controller 704. The support exiting module 726imports the most recently refined patient profile data relating tosupport exiting from facility master 702 so as to be locally stored atin room controller 704. Threshold issues include whether patient bedbehavior is restricted and what time periods the restrictions areenforced. If support exiting behavior is not restricted for that patientor within a given time period, support exiting need not be monitored andresponded to, at least within the given time period when the restrictionis not in effect. Only if support exiting restrictions apply within agiven time period does the support exiting module need to function todetect support exiting by the patient.

According to one embodiment, data from a plurality of data channelsrelating to various parts of the patients body are sampled with afrequency sufficiently high to obtain maximal event capture whileminimizing unproductive hardware loads to populate support exitingalgorithms (e.g., at 0.25 second intervals). The data channels containcontinuously flowing data regarding the locations and/or time durationsat specified locations for the patient's head, arms, hands, legs andtorso. The algorithms for each patient are based on specific supportexiting behavior for that patient based on the patient's profile.Examples of profile data relating to support exiting behavior and limitsis set forth in a later section below. The profile data includes or isused to create specific combinations of triggers relating to specificcombinations of body part movements and/or time durations at specificlocations, which are individually populated and flagged if satisfied. Ifthe correct combination of triggers for that patient is metsimultaneously, an actionable event is detected and a response isinitiated.

For example, the following data channels A through H have been assignedto measure the distance between a particular patient body part and acorresponding or related support (e.g., bed) zone and/or the timeduration that a body part is in contact or proximity with thecorresponding or related support zone.

Bed Exit Channels A = head distance from head board (inches) B* = B =head distance right (inches) C* = C = head distance left (inches) D =engagement of right upper bed rail (consecutive seconds) E = engagementof left upper bed rail (consecutive seconds) F = leg within exit zoneright (consecutive seconds) G = leg within exit zone left (consecutiveseconds) H = head height of eleveation (inches)

As discussed below, there are seven common bed exiting behaviors whichare consistent with specific combinations of behaviors corresponding toinformation measured by each of data channels A though H.

Trigger Combinations for Alerts Bed slide A Side rail roll right D and BSide rail roll left E and C Torso up/side rail roll right H and B* Torsoup/side rail roll left H and C* Torso up/leg kick right H and F Torsoup/leg kick left H and G

When a distance or time duration matches information contained within apatient's profile of support exiting behavior, that variable is flagged.When all of the variables for the specific support exiting behavior fora patient are triggered, an alert or alarm may be triggered and aresponse initiated. Different patients may have different trigger valuesfor the various behaviors depending on known support exiting behavior,patient size, and other attributes.

Upon the occurrence of a predetermined combination of behaviorsconsistent with support exiting for a specific patient, an alarm may betriggered and a response initiated. An exemplary support exitingresponse includes: (1) initiating HIPAA notification to the patient ofpotential viewing of video feed of patient; (2) establishing an A/V linkto a nursing station for nurse only viewing of the patient; (3)verifying nurse's presence at the nursing station within an establishedtime response period by the nurse verifying or rejecting whether supportexiting is actually occurring; (4) alternatively initiating an automaticresponse if nurse's presence not verified within time response period;(5) if nurse's response is “reject”, with the option of mandatory staffapproval, modifying the patient profile to loosen support exiting limitsand notifying resident that viewing is concluded; (6) if nurse'sresponse is “accept”, establishing “video stall” A/V link to delaysupport exiting, sending message to assigned PDA and closest nurse PDAof event, beginning nurse floor response time timer (finish when nurseRFID enters requested room), and modifying patient profile to confirm ortighten support exiting limits; and (7) generating bed exit event reportfor each 24 hour period. A more detailed description of support exitingand response is set forth in a later section below.

2. RFID Zone Security Module

As discussed above, the RFID zone security module 710 is typicallylocated in the facility master 702. According to one embodiment, theRFID zone security module 710 scans the RFID zone locations of patients,staff and visitors at a facility at a frequency sufficiently high toobtain maximal event capture while minimizing unproductive hardwareloads (e.g., at 1.0 second intervals). Using profile data, the module710 classifies individual locations as one of: (1) safe, (2) warning or(3) violation. If the location classification is safe, no alerts oralarms are initiated.

In the case where a patient's or visitor's location triggers a“warning”, a timer is initiated. If the location of the individual atissue does not downgrade to “safe” within a prescribed timer interval(e.g., “X” seconds), an alert is sent to the nursing station and a staffresponse timer mode is initiated. The timer runs until the individual isremoved from any restricted RFID zones. The amount of elapsed time canbe used to assess staff performance.

If an individual's location triggers a “violation”, an alert is sent tothe nursing station and possibly security, and a staff response timermode is initiated. The timer runs until the individual is removed fromany restricted RFID zones. The amount of elapsed time can be used toassess staff performance. According to one embodiment, nursing stationstaff can visually and/or verbally instruct the patient or visitor tovacate the restricted area through the use of an A/V interface. Asecurity zone report can be generated every 24 hours if requested.

In order to illustrate how an initial flight risk level for a givenpatient, coupled with monitored behavior, may trigger appropriate alertsand alarms in the case of possible building flight, the followingexample is given. The box below is a grid that illustrates variousdanger zone values surrounding a building exit, with the lower numbersrepresenting geographic zones that are farther away from the exit, andhigher numbers representing geographic zones that are closer to theexit. The danger zone values can be used to calculate a present flightrisk level for each of a plurality of patients as they move toward theexit, which is next to danger zone 8.

3 4 8 4 3 2 3 5 3 2 1 1 2 1 1 1 1 1 1 1 0 0 0 0 0

By way of example, a patient of known normal flight risk might beassigned an initial flight risk score of 10. A patient having a knownhigh flight risk level might be given an initial score of 5. The lowerthe score, the higher the flight risk. Whenever a patient enters a zonehaving a danger zone value that is equal to or greater than the dangervalue of preceding zone, the initial flight risk score is modified bysubtracting the present danger zone value. Thus, if a patient with aninitial flight risk score of 10 enters a flight zone with a danger zonevalue of 1, the patient's current flight risk score is reduced to 9.Entering danger zones of equal or greater value results in furtherreductions in the current flight risk score. An alert of possible flightrisk and A/V intervention may be triggered, for example, if the flightrisk score falls to below a predetermined threshold (e.g., below 4). Analarm is triggered if the flight risk score falls to 0 or below (i.e., anegative number) and direct intervention to prevent or mitigate actualflight is initiated. If, after entering a danger zone with a givenvalue, the patient turns around and enters a danger zone having a lowervalue, the flight risk score can be increased to reflect the lessenedflight risk.

3. Ambulation Tracker Module

As discussed above, the ambulation tracker module 714 is typicallylocated in the facility master 702. According to one embodiment, theambulation tracker module 714 measures the total ambulation distance foreach patient and staff member by determining the total number of RFIDzones occupied by each individual during each 24 hour period andmultiplying that value by the RFID zone size (e.g., 3 feet). Dailyambulation values are buffered to generate weekly averages. Alerts maybe generated when daily values differ from the historical average bymore than 50%. The overall trend for weekly averages can be monitored todetermine the existence of increases or declines in ambulation.Ambulation reports and be generated for patients, staff and visitorsevery 24 hours if requested. Patient health, staff performance andvisitor behaviors can be assessed using ambulation values.

According to another embodiment, ambulation tracker module 714 pollspatient profiles to determine which patients require ambulationassistance devices (e.g., walker, wheelchair or crutches). If so, themodule 714 also tracks the location of any assigned devices for eachpatient using the associated RFID for the device. For the subset ofpatient requiring ambulation devices, determining whether any patientmoves between RFID zones without detecting the presence of the assignedRFID tagged ambulation device. If separation of patient and ambulationdevice is determined, initiating an alert to the nursing station forpossible intervention. Assistive ambulation device reports can begenerated for patients every 24 hours if requested.

The ambulation tracker module 714 can also detect potentially dangerouschanges in patient gait by noting the time it takes for a patient tomove between zones. For example, for a patient who normally passesbetween RFID zones at a particular pace, detecting substantial slowingor unusual movement between zones may be an indication of a seriousmedical condition.

4. Contact Tracker Module

As discussed above, the contact tracker module 712 is typically locatedin the facility master 702. The purpose is to determine and verify theexistence of prescribed patient/staff contacts as they may relate topatient care and wellness and/or staff performance. According to oneembodiment, the contact tracker module 712 polls a patient's profile forall elements that require patient/staff contact to be performed and/ordelivered on a prescribed schedule. Examples include: (1) meals broughtdirectly to rooms—denoted by RFID tagged meal tray; (2) special dietrestrictions—denoted by RFID tagged meal tray; (3) assistance duringmealtimes in room; (4) trips to cafeteria during meal times per day; (5)in-room therapy required without medical device; (6) in-room therapyrequired with one or more devices (i.e. assets) A; (7) in-facilitytherapy/physical therapy; (8) assisted facility exits.

The RFID system 706 is monitored to count each of these events andcompare to prescribed standards set within each patient profile. Thetime period of patient/staff interaction should be measured and comparedto pre-set minima and maxima. Alerts and alarms may be generated if anincreasing degree of poor staff performance is detected. Data generatedby the contact tracker module can be used to assess patient care andwellness and/or staff performance.

5. Socialization Module

As discussed above, the socialization module 718 is typically located inthe facility master 702. The purpose is to determine the degree ofpatient socialization as it may relate to patient care and wellness. Thesocialization module 718 analyzes RFID monitored patient movements andbehaviors and generates either a (+) or (−) influence on a numeric valuethat represents each patient's socialization factor (PSF). PSF maynormally begin at a default value 5 and increase to a maximum of 10 anddecrease to a minimum of 1 depending on patient activities. High, low orchanging PSF are an objective measure of patient wellness.

Exemplary patient activities that count as a possible (+) PSFinfluencing element include: (1) visitors visiting patient's room; (2)assisted exits of facility; (3) other patients to patient's room; (4)trips by patient to other patient's rooms; (5) time in common areas(e.g., cafeteria, courtyard, recreation rooms, etc.) when occupied byvisitors other patients; (6) activation of “family plan” communicationelements; (7) contact time with pets (e.g., “canine therapy”); and (8)time/trips to facility courtyard area.

Exemplary patient activities that count as a possible (−) PSFinfluencing element include: (1) consecutive hours in room alone; (2)missed meals; (3) repetitive ambulation behavior (e.g., walkingback-and-forth or in circles); and (4) decreased levels of dailyambulation. Drastic decreases in PSF below previous values or an RSFbelow a critical minimal limit (e.g., 2) may result in the generation ofalerts and alarms. Periodic socialization reports for each patient canbe generated to assess patient wellness and/or staff or visitorperformance (e.g., letters can be sent to relatives requesting morevisits).

6. Surveillance Controller Module

As discussed above, the surveillance controller module 720 is typicallylocated in the facility master 702. According to one embodiment, thesurveillance controller module 720 monitors RFID, motion detection,video cameras and/or door beam tripping data to detect the entrance ofstaff, patients, or visitors into a patient's room or other privatezone. Upon authorized entry by individuals into a patient's room, asdetected using assigned RFID devices, the surveillance controller module720 initiates A/V monitoring of the patient's room and triggers HIPAAappropriate patient notification. Upon room clearing of RFID signals(other than those which assigned resident) the surveillance controllermodule 720 terminates A/V monitoring.

Upon unauthorized entry by individuals into a patient's room, asdetected by image analysis of video data, motion detection and/or doorbeam tripping data in the absence of properly assigned RFID devices, thesurveillance controller module 720 initiates an alarm at the nursingstation, security is notified, and an event response timer is initiated.The event response timer is terminated when authorized staff RFID entersthe patient's room. The event response time can be used to assess staffperformance. The surveillance controller module 720 time stamps andattaches a patient identifier code to A/V surveillance files, which arestored for a prescribed number of days (e.g., 15 days).

7. Emergency Response Module

As discussed above, the emergency response module 716 is typicallylocated in the facility master 702. The purpose is to notify staff andpatients of a facility emergency and initiate an appropriate response toprevent or mitigate patient harm. Upon confirming the occurrence of afacility emergency (e.g., a fire), a qualified staff member inputs thelocation of the event into the system. The emergency response module 716causes the system to send messages to all patient rooms with evacuationinstructions. The emergency response module 716 tracks the evacuation ofall patients and staff via tracking the movements of assigned RFIDdevices for each patient and staff member. Laptop PC and network accessat locations external to the building can be provided for administrationand emergency response personnel.

8. Mobile Call Button Module

As discussed above, the mobile call button module 722 is typicallylocated in the facility master 702. Patients and staff wear RFIDbracelets that include a manual call button that allows for manualactivation of a secondary RFID transmitter during emergency situations.When an emergency RFID is detected, the mobile call button module 722determines who triggered the alert and where the individual is located.The mobile call button module 722 polls the assigned patient profile fora list of most critical medical conditions. The mobile call buttonmodule 722 transmits information regarding the call for help and anymost critical medical conditions to the closest staff PDA for responseand starts response timer mode. The mobile call button module 722determines if A/V communication is supported in the location of theemergency, and if so, establishes an A/V link between the location and anursing station. At the conclusion of the event, nursing station staffinputs whether or not an actual emergency occurred and the patient'sprofile is updated to note inappropriate emergency call button usage(e.g., ordering room service, using it for social calls, horseplay,etc.).

9. External GPS Integration Module

As discussed above, the external GPS integration module 724 is typicallylocated in the facility master 702. The external GPS integration module724 allows for hand off of patient tracking from the RFID system 706 toGPS when residents travel into an exterior courtyard region of thefacility not equipped with RFID zone sensors and/or in cases of patientwandering or flight. Patient movement toward a courtyard can bedetermined by a patient assigned RFID device entering zones leading tothe courtyard.

The external GPS integration module 724 polls the patient profile forprivilege or limit information, including: (1) courtyard privileges forthe patient; (2) courtyard time of day restrictions; (3) courtyard timeduration outside limits; (4) courtyard maximum outside temperaturelimits; (5) courtyard minimum outside temperature limits; and (6) theassigned GPS transmission code for that patient. If conditions are notmet for courtyard access, the module 724 causes system to alert thenursing station and being a response timer. If conditions are met forcourtyard access, then start courtyard duration timer.

10. Denture Tracker Module

As discussed above, the denture tracker module 708 is typically locatedin the facility master 702. According to one embodiment, the denturetracker module 708 ensures that prescribed denture cleaning schedulesare maintained. By means of denture embedded RFID devices, track thetime period between denture RFID occupying RFID zone dedicated todenture cleaning station. Cleaning dentures too often or tooinfrequently can be noted in an appropriate report. Tracking propercleaning of dentures is a measure of patient care and wellness.

According to another embodiment, the denture tracker module 708 ensuresa proper match between an upper denture, lower denture, and the patient.It does so by tracking the locations of patients and correspondingdentures. For example, the denture tracker module 708 may determinewhether a denture RFID that is changing zones (i.e., moving) belongs tothe patient moving through equivalent RFID zones. If not, the module 708sends an alert nursing station and generates a report.

Other assets can be tracked and matched with assigned patients insimilar fashion.

B. Exemplary Profiles

1. Patient Profile

The type of data contained in a patient profile can be selected,populated and modified as required depending on any desired care andwellness criteria and/or learned information. The following patientprofile is merely one example of a suitable profile for use incollecting and processing data by the modules described above. It isgiven by way of example, not by limitation. Each line represents anindependent inquiry that can be analyzed using one or morecomputer-monitored data channels. Data may be static or dynamic. Dynamicdata can either by altered automatically or manually.

1. bed exit monitoring required - (y/n), S 2. evening bed boundinitiation time - xx:xx, S 3. morning bed bound termination time -xx:xx, S 4. limit on head to head board distance - x inches, AD tighten,MD loosen 5. number of bed slide exit attempts - #, AD 6. limit on righthand bedrail loading - x seconds, AD tighten, MD loosen 7. number ofright side bedrail exit attempts - #, AD 8. limit on left hand bedrailloading - x seconds, AD tighten, MD loosen 9. number of left sidebedrail exit attempts - #, AD 10. limit on head elevation - x inches, ADtighten, MD loosen 11. number of torso up/bedrail roll exit attempts -#, AD 12. dietary restrictions - (y/n), S 13. diabetic foodrestrictions - (y/n), S 14. soft food restrictions - (y/n), S 15.in-room assistance required during eating - (y/n), S 16. number of tripsto cafeteria during breakfast/lunch/dinner time periods per day - #, AD17. assisted turning in bed per evening time block - #, AD 18.unassisted turns in bed per evening time block - #, AD 19. socializationcounter - 1 to 10 scale, AD 20. hallway gait timer - x minutes, AD 21.total daily ambulation counter - x minutes and y distance, AD 22. weeklyambulation average - x minutes and y distance, AD 23. total daily(ambulation with assistive device) counter - x minutes and y distance,AD 24. weekly (ambulation with assistive device) average - x minutes andy distance, AD 25. in-room therapy without device - (y/n), S 26. in-roomtherapy with device - (y/n), S 27. staff presentations in room withdevice per day - #, AD 28. ambulation with device mandatory - (y/n), S29. corresponding ambulation device or devices - RFID code, S 30.maxillary denture - RFID code, S 31. mandibular denture - RFID code, S32. denture cleaning schedule counter - # per week, AD 33. bathroom timelimit - x minutes, S 34. courtyard privileges - (y/n), S 35. courtyardtime of day restrictions - xx:xx, S 36. courtyard duration outsidelimit - x minutes, S 37. courtyard maximum outside temperature - x °F./C., S 38. courtyard minimum outside temperature - x ° F./C., S 39.unassisted facility exiting - (y/n), S 40. level of flight risk - #, ADtighten, MD loosen 41. number of authorized facility exits per month -#, AD 42. number of unauthorized facility exits or attempts per week -#, AD 43. facility restricted areas - RFID codes, S 44. inappropriateemergency call button usages - #, AD 45. pet therapy contact - (y/n), S46. critical medical history - [data], S 47. emergency call contact #1,S 48. emergency call contact #2, S 49. emergency call contact #3, S S =Static Parameter AD = Automatically Dynamic Parameter MD = ManuallyDynamic Parameter

2. Staff Profile

The type of data contained in a staff profile can be selected, populatedand modified as required depending on any desired quality or performancecriteria and/or learned information. Staff performance will typicallyrelate in some way to providing patient care and wellness and may differbased on specific attributes, assignments and/or rights of each staffmember. The following staff profile is merely one example of a suitableprofile for use in collecting and processing data by the modulesdescribed above. It is given by way of example, not by limitation. Eachline represents an independent inquiry that can be analyzed using one ormore computer-monitored data channels. Data may be static or dynamic.Dynamic data can either by altered automatically or manually.

1. work schedule - day of week, time of day, S 2. restricted RFIDzones - x, y, z, S 3. assigned resident rooms - x, y, z, S 4. totalambulation - time x and distance y, AD 5. most visited room - time x, AD6. second most visited room - time x, AD 7. third most visited room -time x, AD 8. fourth most visited room - time x, AD 9. fifth mostvisited room - time x, AD 10. sixth most visited room - time x, AD 11.seventh most visited room - time x, AD 12. eighth most visited room -time x, AD 13. ninth most visited room - time x, AD 14. tenth mostvisited room - time x, AD 15. number of facility exits per day - #, AD16. duration of facility exits - minutes x, AD 17. % of total work timespent with patients, AD 18. % of total work time spent with other staff,AD 19. % of total work time spent alone, AD S = Static Parameter AD =Automatically Dynamic Parameter MD = Manually Dynamic Parameter

3. Visitor Profile

The type of data contained in a visitor profile can be selected,populated and modified as required depending on any desired performancecriteria and/or learned information. Visitor performance may relate toattribute and rights of each visitor and also patient care and wellness.The following visitor profile is merely one example of a suitableprofile for use in collecting and processing data by the modulesdescribed above. It is given by way of example, not by limitation. Eachline represents an independent inquiry that can be analyzed using one ormore computer-monitored data channels. Data may be static or dynamic.Dynamic data can either by altered automatically or manually.

1. identification number (drivers license #) - xxxxxx, S 2. biometricscan data, S 3. time of day restriction for entrance - xx:xx, S 4.associated resident RFIDs - x, y, z, S 5. allowed resident room RFIDzones - x, y, z, S 6. generic allowed RFID zones - x, y, z, S 7. genericrestricted RFID zones - x, y, z, S 8. can patient leave facility withvisitor assistance? (y/n), S 9. most visited room - x, AD 10. secondmost visited room - x, AD 11. third most visited room - x, AD 12. fourthmost visited room - x, AD 13. fifth most visited room - x, AD 14. mostcommonly associated human RFID - x, AD 15. second most commonlyassociated human RFID - x, AD 16. third most commonly associated humanRFID - x, AD 17. fourth most commonly associated human RFID - x, AD S =Static Parameter AD = Automatically Dynamic Parameter MD = ManuallyDynamic Parameter

C. Refinement of Profiles

FIG. 8 illustrates a flow chart of a method 800 for maintaining andrefining stored profiles for patients, staff and visitors at ahealthcare facility. Method 800 includes an act 801 of storing aninitial profile for each of a plurality of patients, staff or visitorsat a facility based on at least one of specific personalized informationfor each patient, staff or visitor, or general information common tomore than one individual. The patient profiles may include at least oneof an alarm level for use in triggering an actionable event, a treatmentregimen for the patient, or wellness measurement for the patient. Thestaff and visitor profiles may include initial information relating tostaff and visitor performance as it may relate to the care or wellnessof patients.

Method 800 includes an act 802 of receiving collected data relating toeach of the patients, staff or visitors at the facility. The data can becollected using one or more sensors, I/O devices, cameras or computerspositioned within the facility that detect or provide data regardingmovements by patients, staff, visitors and assets.

Act 803 involves refining the profile of a patient based on thecollected data in order to modify at least one of an alarm level, careor wellness parameter, or a treatment regimen for the patient. Thepatient profile can be updated by way of an information feedback loop inwhich potentially actionable events are confirmed or denied throughhuman intervention. In some embodiments, stored patient profiles arerisk profiles that include recursively refined patient alarms levelsindicative of actionable events requiring a response. Finally, method800 includes an act 804 of refining staff and/or visitor profiles basedon collected data relating to staff and/or visitor performance, whichwill typically relate in some way to ensuring or gauging patient careand wellness.

IV. Systems and Methods for Monitoring Patient Support Exiting andResponse

Monitoring and responding to unassisted patient support exiting is anexample of a specific care and wellness parameter. It helps increase theoverall quality and performance of a facility. Potential support exitingcan be monitored by determining the location of a patient, particularlythe location and/or time duration of specific body parts relative tofixed locations. Detecting potential patient support exiting in advanceof actual support exiting gives a caregiver the opportunity to interveneand prevent support exiting, assist support exiting, or mitigate patientharm.

FIG. 9 is a diagram that schematically illustrates an exemplarycomputer-controlled system 900 for patient monitoring, more particularlywith respect to potential patient support exiting, detecting a positionand/or movement of a patient that is predictive of support exiting,obtaining human verification of actual support exiting, and interveningif support exiting is confirmed. The patient monitoring system 900includes a patient room 902 containing a bed 904 or other support and apatient 906 resting thereon at least some of the time. One or moreoverhead cameras 908 may be provided that provide an aerial view ofpatient 906 together with one or more side or lateral view cameras 910.The overhead camera 908 is especially useful in monitoring lateral(i.e., side-to-side) and longitudinal (i.e., head-to-foot) patientmovements, although it may also monitor other movements. The lateralview camera 910 is especially useful in monitoring longitudinal and upand down movements, although it can monitor other movements. The lateralview camera 910 and/or other camera (not shown) can be positioned tomonitor and record a patient room door 912 or other access point (e.g.,to detect and/or record entry and/or exit of personnel, other patients,or visitors). The bed 904 may include markings (e.g., decals) (notshown) that assist in properly orienting the cameras to fixed referencepoints. The markings may assist in determining the distance between afixed point and body part.

The room 902 also includes an audio-video interface 914 that can be usedto initiate one-way and/or two-communication with the patient 906.According to one currently preferred embodiment, A/V interface 914 ismounted to a wall or ceiling so as to be seen by patient 906 (e.g.,facing the patient's face, such as beyond the foot of the patient'sbed). The A/V interface 914 may include any combination of a videomonitor (e.g., flat panel screen), a camera mounted adjacent to thevideo monitor (e.g., below), one or more microphones, and one or morespeakers. The A/V interface may form part of a local computer system(e.g., an “in room controller”) that controls the various sensors andcommunication devices located in the patient room.

In order to analyze patient movements that may be predictive of support(e.g., bed) exiting, video data streams 916A and 918A are sent fromcameras 908 and 910, respectively, to a computer system 920 foranalysis. According to one currently preferred embodiment, at least aportion of the computer system 920 is an in room controller associatedwith the patient room 902. In the case where each patient room has itsown in room controller, patient monitoring and analysis of multiplepatients can be simultaneously performed in parallel by dedicated inroom controller computers. Nevertheless, at least some of the tasks,information gathering, and information flow may be performed by a remotecomputer, such as a central facility master computer. The computersystem 920 may therefore include multiple networked computers, such anin room controller, facility master, and other computers. The computersystem 920 includes or has access to a data storage module 922 thatincludes patient profiles 924 (e.g., stored and updated centrally in thefacility master and used locally by and/or uploaded to the in roomcontroller).

A comparison module 926 of the computer system 920 analyzes the videostreams 916A, 918A and, using one or more algorithms (e.g., that may beknown in the art or that may be developed specifically for this system),determines the location and/or any movements and/or duration of bodypart action of patient 906. This information is compared to patientspecific profile data 925 from a patient profile 924 that corresponds topatient 906. In the absence of predicted support exiting or othertriggering event, video streams 916A and 918A are typically not viewedby any human but are actively deleted or simply not stored or archived.This helps protect patient privacy.

When one or more locations, durations and/or movements of patient 906match or correlate with profile data 925 predictive of support exitingby patient 906, the computer system 920 sends an alert 928 to a centralstation 930 (e.g. nursing station) that patient 906 may be attempting toexit support 904. In addition to the alert 928, at least one of videostreams 916B, 918B from cameras 908, 910 and/or a modified video stream(not shown) from computer system 920 is sent to an A/V interface 934 atcentral station 930 for human verification of actual patient supportexiting. The patient 906 is advantageously notified of potential activeviewing by staff to satisfy HIPAA regulations (e.g., by a chime,prerecorded message, e.g., “camera is actively viewing”, or visualindication, e.g., flashing or illuminated words, TV raster pattern). Aprovider 932 views the video stream(s) from patient room 902, determineswhether the patient 906 is in fact preparing to exit the bed 904 orother support, and provides verification input 936 to an appropriateinterface device (not shown) at station 930, which sends verification938 to the computer system 920. Verification 938 may either confirm orreject actual patient support exiting. When viewing is terminated, thepatient may be notified of this fact by, e.g., a tone or pre-recordedmessage (“active viewing is terminated”).

If the provider 932 determines and verifies that actual patient supportexiting is occurring or about to occur, the in room controller, facilitymaster, or other appropriate module or subsystem component withincomputer system 920 sends a notification 940 to a responder 942 toassist the patient 906. Notification 940 may be sent by any appropriatemeans, including an audio alert using a PA system, a text and/or audiomessage sent to a personal device carried by responder 942, a telephonealert, and the like. A tracking system 943 that interfaces orcommunicates with the computer system 920 (e.g., the facility master)may be used to identify a caregiver 942 who is assigned to patient 906and/or who is nearest to patient room 902. In this way, direct physicalassistance to patient 906 who may be attempting to exit support 904 canbe provided quickly and efficiently.

In addition to or instead of sending notification 940 to responder 942,one- or two-way A/V communication 944 can be established betweenprovider 932 at central station 930 and patient 906 (e.g., by means ofA/V interfaces 914 and 934). This allows provider 932 to talk to patient906 in order to provide instructions or warnings regarding supportexiting, possibly to distract patient 906 and delay or prevent supportexiting (e.g., “why are you getting out of bed?”). This may allowresponder 942 to more easily intervene prior to actual support exitingso as to prevent or better mitigate potential harm to patient 906. Apre-recorded audio and/or A/V message 946 may alternatively be sent toA/V interface 914 in patient room 902 instead of direct A/Vcommunication between provider 932 and patient 906.

In the event a provider 932 is not present at central station 930 orotherwise fails to provide verification 938 regarding predicted supportexiting within a prescribed time period, the computer system 920 mayinitiate an automated response in order to prevent or mitigate potentialharm to patient 906. This may include one or both of sendingnotification 940 to a responder 942 regarding possible support exitingand/or sending a pre-recorded message 946.

Verification 938, whether confirmation or denial of actual supportexiting, can also be used to update the patient profile 924corresponding to patient 906. Updated profile data 948 based on one ormore support exiting events can be input or stored at data storagemodule 922. If a particular behavior is found to accurately predictsupport exiting by patient 906, the patient profile 924 can be updatedto confirm the accuracy of the initial profile 924. In some cases,limits within the patient profile 924 may be tightened to be moresensitive to movements and/or durations of actions that have beenconfirmed to correlate with and accurately predict support exiting. Thismay be done manually by authorized personnel or automatically by thecomputer system 920. If, on the other hand, a particular behavior isdetermined to falsely predict support exiting by patient 906, thepatient profile can be updated to note incidences of such falsepositives. Limits within the patient profile 924 can be loosened oreliminated relative to movements that have been found not to correlatewith support exiting by patient 906. In the event support exiting bypatient 906 occurs but is not detected by the computer 920, limitswithin the patient profile 924 can be established and/or tightened in aneffort to eliminate false negatives of support exiting by patient 906.Updating the profile 924 of patient 906 to more accurately predictsupport exiting and reduce or eliminate false positive and falsenegatives substantially increases the reliability of the patientmonitoring system as compared to conventional systems that do notdistinguish between and among support exiting habits or behaviors ofdifferent patients. The foregoing is an example of the use of aninformation feedback loop to refine a patient profile.

In order to later view and/or analyze a triggering event as may beestablished by a facility, video data 950 that is the same as, or whichmay be derived from, one or both of video streams 916, 918 can be storedwithin an archive 952. Archive 952 may comprise any storage media knownin the art of video recording and storage, examples of which includehard drives, optical storage devices, magnetic tapes, memory devices,and the like. The triggering event need not be support exiting but maybe entry into the patient's room by staff, other patients or visitors,or activation of the emergency call button by the patient.

FIGS. 10A and 10B schematically illustrate various embodiments ofexemplary patient room configurations used in monitoring a patient andproviding one or more responses. In the embodiment of FIG. 10A, anexemplary patient room 1000 is illustrated which includes a patient1002, a bed 1004 or other support upon which the patient 1002 rests atleast some of the time. The patient 1002 may wear or carry a mobileelectronic tracking device, such as an RFID bracelet or other device1006. This allows a facility master computer and/or in room controllerto identify and track the location of patient 1002 by means ofelectronic tracking systems known in the art. RFID device 1006 isspecially assigned to patient 1002 and provides verification whenpatient 1002 is located in room 1000. This facilitates using the correctpatient profile when interpreting movements of patient 1002.

One or more overhead cameras 1008 are positioned above the bed 1004 andso as to provide an aerial (e.g. bird's eye) view of patient 1002. Onemore side or lateral view cameras 1010 are positioned to the side ofpatient 1002 to provide a different data stream for determining thepatient's position and/or movements. Camera 1010 may have a direct orperipheral view of a door 1018 or other entrance to room 1000. An inroom controller computer (IRCC) 1012, which may be a local computerlocated in room 1000, analyzes video data streams generated by cameras1008, 1010. A flat panel monitor 1014 (e.g., high definition),controller mounted camera 1016, and optionally other devices such asmicrophones and speakers (not shown) are interfaced with IRCC 1012.

The IRCC 1012 is used to determine the location of the patient's body,including specific body parts, by interpreting video data streamsgenerated by one or more of the cameras 1008, 1010, 1016 and comparingrelative distances between the patient's body and fixed locations (e.g.,the patient's head and the headboard of the bed, the patient's arms andlegs relative to respective left and right bedrails, the height of thepatient's torso relative to the bed, etc.). A changing body partposition indicates movement of that body part. The IRCC 1012continuously or periodically compares the location and/or any movementsof the patient's body or portion thereof with locations and movementsthat are predictive of patient bed exiting by that patient as containedin the patient's profile of bed exiting behaviors. Whenever the uniquesingular or combination of positions, movements, and/or duration ofpositional actions is detected that is consistent with a unique bedexiting behavior, an appropriate response is initiated.

The flat panel video monitor 1014 can provide multiple functions,including providing normal television programming, recorded programmingrequested by the patient 1002, video feeds to remote locations (such asloved ones or staff who wish to communicate with patient 1002 remotely),emergency situation instructions and special messages (e.g., patientalerts). The controller mounted camera 1016 provides a direct facialview of the patient and, in combination with video monitor 1014,facilitates two-way A/V communication between patient 1002 andindividuals outside room 1000. As shown, the camera 1016 may also have adirect view of door 1018 or other room entrance to monitor entry andexit of individuals (e.g., staff 1042, other patients or visitors) fromroom 1000. Camera 1016 may also have a view of bathroom door 1020 tomonitor movement of patient 1002 to and from the bathroom. A standardmotion sensor integrated with conventional video cameras (e.g., camera1016) may provide motion detection means for detecting room entry orexiting activity. Video data from room viewing video cameras, such ascamera 1016, or combinations of room based video cameras, may also beutilized by image analysis programs running within in-room controller1012 to detect and count the number of individuals within the room. Whencombined with in-room counts of residents, staff and visitors from RFIDdata, this information can be used to detect unauthorized entry intopatient's room and therefore positively impact patient wellness.

The room 1000 may include other auxiliary devices, such as bedside callbutton 1022, patient pain scale interface 1023, bathroom call button1024, microphones/speakers 1025, and bathroom motion sensor 1026. Callbuttons 1022, 1024 may comprise those known in the art. The pain scaleinterface 1023 allows a patient to indicate to the monitoring system(e.g., IRCC 1012, facility master, and/or nursing station) the patient'scurrent pain level (e.g., on a scale of 1 to 10, with 1 being the leastand 10 being the most pain). Motion sensor 1026 can be used, e.g., incombination with camera 1016, call button 1024 and/ormicrophones/speakers 1025, to determine whether a patient 1002 requiresfurther assistance while in the bathroom. An RFID grid set up throughoutthe it room can be used to monitor the position and/or movements of thepatient 1002 when not resting on the bed 1004 and also the positionand/or movements of staff 1042, other persons such as patients, friends,family or other visitors, and assets (not shown).

FIG. 10B illustrates an exemplary patient room 1000 which includes apatient 1002, a bed 1004 or other support upon which the patient 1002rests at least some of the time, and various other devices used tomonitor the patient and the patient's room 1000. The patient 1002 maywear or carry a mobile electronic tracking device, i.e., mobile patientlocation client 1006. This allows a facility master computer to identifyand track the location of the patient 1002 by means of electronictracking systems known in the art. Patient location client 1006 may be aconventional RFID device (e.g., bracelet) and may be equipped with apatient emergency call or panic button (not shown) as known in the art.Mobile patient location client 1006 is specially assigned (and attached)to patient 1002 staying in patient room 1000. Client 1006 providesverification that patient 1002 is actually located in room 1000. Thisfacilitates using the correct patient profile when interpretingmovements of patient 1002 rather than those of another patient.

High risk motion clients 1008A and 1008B (e.g., which include one ormore of cameras, electronic motion sensors, electric eyes, RFIDdetectors, etc.) may be positioned on either side of bed 1004, thusproviding two separate data streams for interpretation of the patient'sposition and/or movements. Side cameras 110A and 1010B are positioned oneither side of patient 1002 to provide additional data streams forinterpretation of the patient's position and/or movements. At least oneof cameras 1010A and 1010B may have a direct or peripheral view of adoor 1011 or other entrance to room 1000. An in room controller client(IRCC) 1012, which can be a local computer located in or near room 1000,at least partially controls motion clients 1008A and 1008B, cameras1010A and 1010B, and other electronic devices in room 1000. IRCC 1012also analyzes video data generated by cameras 1008, 1010 in order toidentify behavior of patient 1002 that may be predictive of supportexiting.

Other electronic devices include an in-room A/V interface client 1014,which can be used to establish one- or two-way communication withpatient 1002, patient care client 1016, external A/V client 1018 (e.g.,in a hallway), bathroom interface 1020 (e.g. call button, microphoneand/or speaker), and manual patient interface client 1022 (e.g., a callbutton, pain scale dial, etc.). The room is shown having a chair 1024 orother furniture (e.g., wheel chair), upon which visitors or even thepatient may rest at least some of the time. The monitoring system can beused to detect potential support exiting by patient 1002 ofchair/furniture 1024 in addition to bed 1004.

The IRCC 1012 and electronic devices in room 1000 can interoperate toimplement the principles of the present invention. High risk motionclients 1008A and 1008B, either alone or in combination with one or bothof cameras 1010A and 1010B, can monitor a patient's movements in bed1004 and/or chair or other furniture 1024. Generally, a patient'smovement on a bed or other support can be monitored through a gridmonitoring system (“GMS”) that identifies patient vertical andhorizontal movements that may be indicative of an attempt to exit thefurniture. The time a body part is located within a critical zone and/orchanges in position and/or changes in speed can all be determined. TheGMS can also utilize pressure, temperature, and other distributedsensors located within a bed or other furniture or directly attached toa patient. Inputs from the various clients and sensors in room 1000 canbe provided to the IRCC 1012 and/or facility master (not shown). Inaddition, any of cameras 1010A, 10100B or 1020, as well as motionclients 1008A and 1008B, can monitor a patient's position and/ormovements within room 1000 when the patient is not resting on a bed1004, chair 1024 or other support located in room 1000.

Upon activation of the GMS or other high risk motions clients, in roomcontroller client 1012 and/or a facility master utilizes patientmanagement software to initiate and establish responsive actions. Forexample, upon detecting activities that predict an unattended supportexit, in room controller 1012 and/or a facility master can establish areal time A/V connection with a central station (e.g., nurse's) and/orone or more mobile caregiver clients (e.g., PDAs carried by respondercaregivers). Further, in room controller client 1012 and/or a facilitymaster can activate external A/V client 1018 (e.g., an alarm in ahallway) and/or initiate archiving of data from one or more of high riskmotion clients 1008A and 1008B, and cameras 1010A, 1010B and 1020 uponthe occurrence of a support exiting event or other pre-establishedtriggering event.

FIG. 10B further depicts a provider location client 1026 (e.g., an RFIDdevice), a provider PDA 1028, a provider ID tag 1030 (e.g., an RFIDdevice), other facility ID tag 1032 (e.g., an RFID device), and/ordiagnostic equipment 1034 which have entered room 1000. Each of thesedevices can communicate with IRCC 1012 and/or a system-wide trackingsystem that communicates direct to a facility master computer (notshown) via various appropriate protocols (e.g., RF, IEEE 802.11 group,IEEE 802.15.4, etc.). IRCC 1012 can update pertinent patientinformation, such as, for example, provider ID, other personnel ID ordiagnostic equipment and time of entry. Detecting the presence ofpersonnel and devices inside room 1000 indicates that facility personneland/or assets associated with these devices have likely entered room1000, for example, in response to a predicted support exiting event, apatient initiated alarm, prescribed patient activities, and the like.

According to one embodiment, patient room 1000 may be networked withother components including, for example, subscription clients (e.g.,subscription A/V web browser interface client 1040 and subscription A/Vvoice and video over IP client 1042), which are connected to in roomcontroller client 1012 by means of network 1044. Subscriber clients 1040and 1042 can be located at or external to a healthcare facility. Thus,providers in diverse locations can be notified of actionable eventsoccurring inside patient room 1000.

FIG. 11A illustrates an alternative embodiment for detecting patientsupport exiting behavior comprising a light beam matrix system 1101,which may be used instead of or in addition to one or more cameras usedto determine patient position and/or movements. Exemplary light beammatrix system 1101 includes a patient 1102 resting on a bed 1104 orother support. A plurality of light transmitters 1160 are positioned atone side of bed or other support 1104 and generate first beams of light1162, which are detected by corresponding first light receivers 1164. Aplurality of second light transmitters 1166 are positioned laterallyrelative to first light transmitters 1160 and generate second beams oflight 1168, which are detected by corresponding second light receivers1170. Beams of light 1162, 1168 may comprise IR, visible or UVwavelengths.

First and second beams of light 1162, 1168 may be positioned above thepatient 1102 and cross-cross to form a light beam matrix that is able todetect patient location and/or movement in multiple (e.g., three)dimensions. The closer together the light beams, the finer the detectionof patient position and/or movement. According to one embodiment, thelight beams are spaced apart at intervals ranging from six (6) inches totwo (2) feet (e.g., at one (1) foot intervals). As long as the patient1102 rests flat on the bed or other support 1104 or is otherwise belowthe light beam matrix comprising first and second light beams 1162,1168, no beams of light are blocked or interrupted such that no movementis detected. Interrupting and/or resuming one or more beams of light maybe indicative up upward and/or downward movement(s). Sequentiallyinterrupting and/or resuming one or more of first light beams 1162 maybe indicative of lateral movement(s). Sequentially interrupting and/orresuming one or more of second light beams 1162 may be indicative oflongitudinal movement(s).

A computer system (not shown) interprets data generated by the lightbeam matrix. Continuous light detection by the light sensors may beinterpreted as a series of 1 s (or 0 s) in computer language. Anyinterruption or blocking of a light beam corresponds to a series of 0 s(or 1 s) in computer language and is indicative of a body part beingpositioned between one or more particular light transmitters anddetectors. Because bed exiting, for example, involves at least somelifting of the patient's body (e.g., to get over bed rails or passthrough a narrow passage in a bed rail), actual lifting of the patient'sbody will typically block or interrupt at least one light beam.Depending on which light beams are interrupted and/or the sequence ofsuch interruption, the computer can determine which parts of thepatient's body have raised and/or moved. Sequentially interruptingmultiple beams typically indicates movement (i.e., lateral,longitudinal, upward and/or downward depending on which sequence ofbeams are interrupted). The patient's movements, as detected by thelight beam matrix and interpreted by the computer system, are comparedto a patient profile of positions and/or movements that are predictiveof support exiting by that patient. If potential patient support exitingis detected, an appropriate response can be initiated.

FIG. 11B illustrates an alternative embodiment for detecting patientsupport exiting behavior comprising a small zone RFID grid system 1103,which may be used instead of or in addition to one or more cameras usedto determine patient position and/or movements. Exemplary RFID gridsystem 1103 includes a patient 1102 resting on a bed 1104 or othersupport. The patient's body may be equipped with any appropriate numberof RFID devices that are located so as to detect patient positionsand/or movements associated with support exiting (e.g., right RFID wristdevice 1106A, left RFID wrist device 1106B, right RFID ankle device1106C, left RFID ankle device 1106D, and neck RFID device 1106E). EachRFID device can be separately encoded to represent a specific body partof the patient to distinguish between positions and movements of thedifferent body parts.

The RFID grid system 1103 includes a three-dimensional grid of small,cube-like RFID zones defined by a plurality of RFID detectors positionedalong lateral zone boundaries 1180, longitudinal zone boundaries 1182,and elevation zone boundaries 1184. The closer together the RFIDdetectors, the finer the detection of patient position and/or movement.According to one embodiment, the RFID detectors are spaced apart atintervals ranging from six (6) inches to two (2) feet (e.g., at one (1)foot intervals). The grid of RFID zones is able to detectthree-dimensional patient position and/or movements as approximated bythe positions and/or movements of the RFID devices 1106 worn by thepatient in or through the RFID zones.

A computer system (not shown) interprets data generated by the smallzone RFID grid as it detects the position and/or movement of the RFIDdevices 1106 attached to the patient 1102. Depending on which RFID zoneis occupied by a specific RFID device and/or which RFID device(s) may bemoving between RFID zones, the computer can determine the positionand/or location of corresponding body parts of the patient. If potentialpatient support exiting is detected, an appropriate response can beinitiated.

FIG. 12 is a flow chart that schematically illustrates an exemplarymethod 1200 of monitoring a patient in order to detect support exitingand initiate a response in the event of predicted support exiting. Thismethod may be carried out at least in part using the exemplary patientmonitoring systems illustrated in FIGS. 3, 9, 10A-B and 11A-B discussedabove and/or systems illustrated or discussed elsewhere in thisdisclosure and/or systems or components known in the art. A first act orstep 1201 involves creating or obtaining a plurality of patientprofiles, each containing personalized information relating to supportexiting behavior for each patient.

Examples of known bed exiting behaviors that have been observed as beingused by one or more patients include, but are not limited to: (1) bedslide method (e.g., sliding down towards the bottom of the bed); (2)right side rail roll method; (3) left side rail roll method; (4) torsoangle up and leg swing right method; (5) torso angle up and leg swingleft method; (6) torso angle up and upper body roll right method; and(7) torso angle up and upper body roll left method. A given patient mayutilize one or more of the foregoing methods or a variation thereof, buttypically one will dominate. Other support exiting behaviors arepossible and can be accounted for where relevant.

Reference is now made to FIGS. 13A-13E which illustrate exemplarypatient behaviors as they relate to normal resting and bed exiting. FIG.13A schematically illustrates a normal resting position of a patientlying flat on a bed. FIGS. 13B-13E schematically illustrate positionsassociated with various bed exiting positions, movements or behaviors.FIG. 13B roughly depicts the position of a patient that has engaged inthe bed slide method of bed exiting. A notable feature is the distancebetween the patient's head and the pillow or headboard. FIG. 13C roughlydepicts left and right side rail roll methods in which the patient'sbody moves to the side or left side rail preparatory to bed exiting.FIG. 13D illustrates the torso up and leg swing left method of bedexiting, which is characterized by upward movement of the torso coupledwith movement of the left leg toward the edge of the bed. The torso upand right leg swing method is simply the mirror image of that shown inFIG. 13D. FIG. 13E illustrates the torso up and upper body roll leftmethod, which is characterized by the patient's torso moving upward andthe patient's body rolling to the left. The torso up and upper body rollright method would be the mirror image of that shown in FIG. 13E.

Each patient profile contains one or more spatial parameters or limitsassociated with the one or more support exiting behaviors that are knownfor each patient. The spatial parameters or limits relating to bedexiting may include data points pertaining to one or more of the sevencommon bed exiting behaviors noted above. Image parameters relating toexiting of other supports can be tailored to behaviors that are typicalfor patients exiting such supports. Patient profiles may includeidiosyncratic information that is specific to a particular individual(e.g., base on patient height, weight, speed of movement, length oflimbs, number of operable limbs, and/or personal habits of positionand/or movement while support exiting).

By way of example, as illustrated a spatial parameter that correspondsto the bed slide method of bed exiting is the distance from a headfeature to the top of the bed (e.g., headboard) (see FIG. 13B). Spatialparameters corresponding to the side rail roll methods (left or right)for bed exiting include: (a) the torso positioned primarily to the rightor left of the bed and (b) the hand and/or arm on or over (i.e.,covering or blocking the view of) the left or right bed rail for a givenperiod of time (see FIG. 13C). Spatial parameters corresponding to thetorso up and leg swing methods (left or right) of bed exiting include:(a) the head elevated from a flat position and (b) right or left legsand/or feet breaking a vertical bed edge plane (see FIG. 13D). Spatialparameters corresponding to the torso up and upper body roll methods(left or right) of bed exiting include: (a) the head elevated from aflat position; (b) torso positioned primarily to the right or leftportion of the bed; and one or both of (c₁) the left or right handand/or arm on or over (i.e., covering or blocking the view of) the leftor right bed rail for a given period of time and/or (c₂) the headbreaking a vertical plane of the left or right side rail (see FIG. 13E).In addition to patient body position, time of duration of a limb or bodypart at a specified location relative to a critical region of thesupport may also play a roll in determining bed or other supportexiting.

Referring back to FIG. 12, a second act or step 1202 of method 1200involves associating a corresponding patient profile with the particularpatient being monitored. The use of RFID or other patient identificationand tracking devices may assist in identifying which patient profilecorresponds to the patient being monitored. For example, if a patientmoves from room to room over time, different monitoring equipment in thevarious rooms can all monitor the same patient at different times, whilecomparing patient position and/or movements with specific profile datafor that patient, because the patient is associated with a patientidentification and tracking device that emits a uniquely encoded signal.Such association may alternatively be made (e.g., entered manually intoa computer) by hospital staff whenever a patient occupies a particularroom.

A third act or step 1203 of method 1200 involves continuously monitoringa patient resting on a support by capturing a series of images of thepatient and surroundings and sending a data stream (e.g., video feed) toa computer system for analysis. Since both motion video recordingdevices and still photo devices are capable of taking individual frames,the distinction between the two is simply the speed with whichindividual frames are taken (i.e., the time interval between frames).Thus, both motion video recording devices and still photo devices can beused to send a continuous data stream to the analyzing computer system.

A fourth act or step 1204 of method 1200 involves analyzing the datastream (e.g., frames of video data) to determine patient position and/ormovement and comparing them to patient profile data relating to thesupport exiting behavior of that patient. As discussed above, suchcomputer-implemented analysis of position and/or movement may be carriedout using a grid monitoring system (GMS), which compares the relativeposition of one or more body parts in relation to stationary backgroundobjects, such as critical or predefined support zones. The use ofpatient specific profiles enables the computer system to more accuratelydetect and distinguish between behaviors that are indicative orpredictive of patient support exiting and those which are not ascompared to methods that are not patient specific but utilize the samesets of analytical limits for all patients. In this way, the incidencesof false positives and false negatives are significantly reduced orsubstantially eliminated.

In the event that behavior consistent with predicted support exiting isdetected, a fifth act or step 1205 of method 1200 is triggered. Step1205 includes initiating an appropriate response in an attempt toprevent or mitigate harm to the patient. Exemplary responses includesending an alarm and/or video feed to a nursing station, alerting thepatient of potential viewing, establishing one- or two-way communicationbetween the patient, sending a pre-recorded message to the patient,sending notification to a nearby caregiver who can provide directphysical intervention, sounding an alarm, and the like. It may even beappropriate in some cases to activate an automated restraint device thatis able to keep the patient from exiting the support until a caregiveris able to arrive and provide assistance.

The method optionally includes an act or step 1206 of refining thepatient's profile to adjust one or more alert triggers to reflectmonitored bed exiting behavior. In this way, the profile may beprogressively refined to reflect a patient's historical support exitingbehavior as monitored over time. This would be expected to decrease theoverall number of false positives and false negatives, which would tendto increase the accuracy and efficiency of responding to potentialsupport exiting behaviors on the part of the patient.

FIG. 14 is a flow chart that schematically illustrates an exemplarymethod or sub-routine 1400 of generating and updating a patient profilefor support exiting behavior. A first act or step 1401 involves settinginitial support exiting limits based on information learned from orabout the patient (e.g., as a result of a patient or relative completedquestionnaire, observation by a qualified provider, general defaults,and the like). It is understand that the initial limits areadvantageously modified as more information is gathered over timeregarding a patient's actual support exiting habits while at one or morefacilities.

Accordingly, a second act or step 1402 includes actually monitoring apatient while resting on a support as discussed above and then eitherconfirming or rejecting an alert of predicted patient support exiting.From one or more confirmations or rejections of predicted bed exiting,additional information regarding the specific support exiting habits ofthe patient can be learned. Act or step 1402 may form part of aninformation feedback loop for recursively refining patient profile data.

A third act or step 1403 includes manually or automatically revising orupdating previously set support exiting limits in order to moreaccurately predict support exiting behavior by patient in question. Insome cases, the computer system may appropriately alter patient profiledata and limits relating to bed exiting so long as it does notsubstantially increase the risk of unassisted support exiting. In othercases, patient profile data and limits relating to bed exiting may bealtered manually by a qualified individual or committee who analyzesdata generated during predicted support exiting events. Limits can beestablished initially, or pre-existing limits may be tightened orloosened, in response to incidences of false positives and/or falsenegatives relative to support exiting.

FIG. 15 is a flow chart that schematically illustrates an exemplarymethod or sub-routine 1500 of responding to predicted patient supportexiting. In a first act or step 1501, a computer system finds acorrelation between a patient's location and/or movements andpredetermined limits for that patient contained in or derived from apatient specific profile. A second act or step 1502 involves a computerinitiating a response by sending an alert to both the patient's room (towarn of a breech in privacy) and a nursing station along with a live(i.e., real time) video feed of the patient's room to the nursingstation. In a third act or step 1503, a staff member at the nursingstation confirms or rejects the predicted support exiting upon viewingthe live video feed of the patient's room. In a fourth act or step 1504,if support exiting is confirmed, a computer-controlled tracking systemlocates an unoccupied staff member who is assigned and/or near thepatient's room and instructs the staff member to assist the patient.

FIG. 16 is a flow chart that schematically illustrates an exemplarymonitoring and response decision chart 1600 relative to bed exiting. Thepatient is continuously or periodically monitored, and the patient'sposition and/or movements are analyzed. As long as positions and/ormovements predictive of bed exiting are not detected, monitoringcontinues. Of course, monitoring may also continue even after bedexiting is predicted in order to send a live video feed to a centralstation and/or determine an escalation of events.

If predicted patient bed existing is detected by the analyzing computersystem, an alert is sent to a nursing station as well as a live videofeed of the patient for verification of actual bed exiting. Prior to orat the same time, an alert is sent to the patient's room of potentialthird party viewing of the patient (e.g., to protect patient privacy).If no verification (i.e., confirmation or denial) is sent to thecomputer system within a predetermined time period, an automatedresponse is initiated. If verification is sent, the computer determineswhether bed exiting is confirmed or denied. If bed exiting is denied,the computer system resumes normal patient monitoring. If bed exiting isconfirmed, further intervention is initiated.

The escalation of intervention to assist a patient who is in the processof bed exiting may include establishing one- or two-way communicationbetween the confirming staff member and the patient. It may also includesending an alert to a nearby or assigned staff member for directphysical intervention. An RFID or other tracking device can be used toverify that physical intervention was carried out as prescribed. Theassisting caregiver may press a confirm button on a patient careinterface device connected to the computer system, or the caregiver mayprovide oral confirmation to the staff member at the nursing station.The staff member at the nursing station may view the live video feedfrom the patient's room to confirm successful intervention. Ifintervention is confirmed, the response is complete. If intervention isnot confirmed, the response may include sending one or more additionalalerts to other nearby staff members for direct physical intervention.

V. Examples of Other Methods and Systems for Enhancing Quality andPerformance at a Facility

A. Providing Patient Assistance

FIG. 17 a flow chart which illustrates an exemplary method 1700 forresponding to patient alerts and providing assistance for a patient inneed thereof. Method 1700 will be described with respect to thecomponents and data in system architecture 300 (FIG. 3). Method 1700includes an act 1701 of providing the patients of a facility with RFIDdevices, each of which is associated with a specific patient, emits asignal that permits tracking of the specific patient, and includes analert button that, when actuated, sends an alert associated with thespecific patient. For example, as previously described, a patientstaying in a room at the facility can be provided with a mobile patientlocation bracelet specifically assigned to the patient.

Method 1700 includes an act 1702 of receiving one or more signalsemitted by one or more RFID devices so as to track the location ofpatients throughout the facility. For example, sensing devices 312within the facility can receive an RFID signal, an alarm signal, etc.from each mobile patient location bracelet. Each patient can be trackedand located in patient rooms and also throughout hallways, other commonareas, and dangerous or otherwise restricted areas of a healthcarefacility. Signals can be detected by RFID sensors throughout a facilityand relayed to computer systems that process the signals to generateappropriate electronic messages and notifications.

Method 1700 includes an act 1703 that includes, in response to receivingan alert from an RFID device associated with a patient in need ofassistance, identifying the location of the patient, accessing relevantinformation from the patient's profile, and initiating a response (e.g.,a patient specific response that can optionally be tailored based oninformation in the patient's profile, such as the most critical medicalconditions of the patient requesting help). For example, in response toreceiving an alert from a mobile patient location bracelet, the locationof an assigned or nearby caregiver can be identified and appropriatephysical intervention can be initiated. The intervention may bedifferent for different patients based on their respective profiles andmedical conditions. A computer system that processes the signal (e.g.,an in room controller client or facility master) can generate anelectronic message or notification that is sent to one or more otherelectronic devices corresponding to assigned or nearby healthcareproviders (e.g., to computer system 301 c, PDA 309, PDA 309, etc.)

In response to using the alert feature, patient profiles can be updatedto count the number of times each patient has initiated an authorizedalert (e.g., an actual physical or medical emergency) versus anunauthorized alert (e.g., ordering room service, socializing, horseplay,etc.). In order to provide for the specific needs of a patient, patientprofiles data can be accessed and a predetermined or specially tailoredresponse initiated (e.g., in the case of patients with special needs).

B. Selectively Archiving Patient Video Recordings

FIG. 18 is a flow chart that illustrates an exemplary method 1800 forselectively archiving a video recording of a patient in response to atriggering event. Method 1800 will be described with respect to thecomponents in a typical patient room (e.g., room 1000 of FIGS. 10A and10B).

Method 1800 includes an act 1801 of generating a video data stream of apatient's room at a healthcare facility, wherein the video data streamis continuously buffered and then deleted in the absence of a triggeringevent such that the buffered and deleted video recording is normallynever viewed by an individual in order to protect patient privacy. Forexample, a computer system can use a circular buffer of a specified sizesuch that after a prescribed amount of time (e.g., 3 to 5 minutes) oldervideo data is overwritten by new video data within the buffer. By way ofexample, an in room controller and/or facility master can make atemporary or buffered video recording of received video data from one ormore cameras positioned within a patient's room.

Method 1800 includes an act 1802 of selectively archiving thetemporarily buffered video data stream in response to a triggering eventso as to permit later viewing of the archived video recording. Videoarchival data can be stored at a healthcare facility or offsite. Thearchived video recordings are typically merely a back-up that helpsverify the occurrence of a prescribed event and do not constitute a“medical record” within the meaning of HIPAA or other applicablestatutes. By way of example and not by limitation, the triggering eventmay comprise at least one of:

-   -   (i) entry into the room of an authorized RFID device encoded        with entry rights associated with an authorized individual;    -   (ii) entry into the room of an unauthorized RFID device        associated with an unauthorized individual not having entry        rights;    -   (iii) entry into the room of an individual not associated with        any RFID device;    -   (iv) an asset used for a prescribed treatment and associated        with an RFID device being located in the room; and/or    -   (v) any other prescribed triggering event created by a given        healthcare facility.

C. Monitoring Patient Bed Rolling

Image analysis used to monitoring patient support exiting can also beused to monitor patient bed rolling behaviors. With bed-bound patients,skin breakdown, pressure sores and ulceration are important clinicalconcerns. To prevent these conditions from occurring, staff may bescheduled to relieve skin pressure points on the patient's body bymanually turning the patient periodically (e.g., every 2, 3 or 4 hoursas prescribed). This turning schedule disturbs the patient's naturalsleep pattern, increases the risk of injuring the patient during theprocess, and adds significantly to staff workload.

By utilizing the in-room image analysis system to detect, record, countand report patient roll-overs, it will be possible to alert staff as towhich patients require manual rolling over for each time period andwhich do not. Benefits to the patient include better sleep quality andless opportunity for tissue injury due to manual turning. Benefits tothe staff include reduced work load by only turning those patients whoactually require it. To visually verify that a patient has self-turnedadequately during a time period, the system may allow for acceleratedviewing of the buffered or recorded time period with real-speed viewingof detected turning events.

VI. Exemplary System Logic

By way of example only and not by limitation, the inventive systems andmethods for patient, staff and visitor monitoring and response mayemploy the followingC<<exemplary logic:

Assigned Limit Variables

[A] head distance from headboard; initial value = 30″ [B] head elevationfrom flat/down position; initial value = 12″ [C] space between body andbedrail; initial value = 5″ - may need Small/Med/Large Values to reflectPatient body size [D] hand on bedrail time; initial value = 5 seconds[E] bed bound/requires assist for exit; yes = 1, no = 0 [F] patient roomassignment for RFID [G] number of exit attempt for Torso Slide [H]number of exit attempt for Torso Up/Leg Sweep [I] number of exit attemptfor Bedrail Roll [J] number of exit attempt for Unknown Method [K]family members video recorded; yes = 1, no = 0 [L] other residents videorecorded within room; yes = 1, no = 0 [M] resident currently infacility; yes = 1, no = 0 [N] requires movement assistance; yes = 1, no= 0 [O] requires movement assistance every “X” hrs [P] does the residentrequire a special diet; yes = 1, no = 0 [Q] does the resident requireassistance during eating; yes = 1, no = 0 [R] number of RFID presencesin eating area during breakfast, lunch and dinner times per day [S]status of resident social interactions, maximum = 10, minimum = 0 [T]requires device specific therapy every “Y” hrs [U] valid mobileemergency call button usage per month [V] unwarranted mobile emergencycall button usage per month [W] is resident limited to movement withinthe facility; yes = 1, no = 0 [X] is resident limited to movement withintheir room; yes = 1, no = 0

Image Analysis Outputs

(1) top of head to headboard distance (inches)

(2) head elevation from flat position (inches)

(3) leg in bed or out of bed (in/out)

(4) space between body and bedrail (inches)

(5) hand grasping bedrail duration (seconds)

(6) no body in bed (absent/present)

Alert Conditions For Bed Exiting

For all [E]=1

-   Torso Slide=(1)>[A]-   Torso Up/Leg Sweep=(2)>[B] and (3)=out-   Bedrail Roll=(4)<[C] and (5)>[D]-   Bed Exit Has Occurred=(6) is absent and RFID [F] is positive

Action Taken For Positive Exit Alert

check RFID for Staff presence at Nursing Station

-   -   if no—then send pre-recorded message, alarm sent to closest        shell staff RFID PDA, document, and go to Patient Profile Update    -   if yes—then request Alert Verification or Alert Rejection from        staff        -   if neither Verify or Reject is given within 30 seconds then            send pre-recorded message, alarm sent to closest shell staff            RFID PDA, document and go to Patient Profile Update    -   if yes and Alert Verification is Positive then        -   alarm sent to closest shell staff RFID PDA        -   Video/Audio link established with Nursing Station        -   Patient Profile is Updated    -   if yes and Alert Rejection is Positive then        -   Possible Patient Profile Update (loosen alert criteria)

Patient Profile Update For Bed Exiting

[A]=[A]−[G] until [A]=20″ then [A]=[A]

[B]=[B]−[H] until [B]=6″ then [B]=[B]

[C]=[C]+([I]/3) until [C]=9″ then [C]=[C]

[D]=[D]−([I]/3) until [D]=2 seconds then [D]=[D]

In-Room Camera Record On/Off Control

Camera Record is OFF until triggered by one of the following Actions:

-   -   1. For [K]=yes and [L]=yes, the detection of an RFID that        doesn't match with [F]    -   2. For [K]=no and [L]=yes, the detection of an RFID that doesn't        match with [F] and is not a Family RFID    -   3. For [K]=yes and [L]=no, the detection of an RFID that doesn't        match with [F] and is not a Resident RFID    -   4. For [K]=no and [L]=no, the detection of an RFID that doesn't        match with [F] and is not a Resident RFID or a Family RFID    -   5. Alternatively for 3. and 4., a numeric coded “CAMMERA OFF”        control pad could be accessible for each resident in each room        then 3. and 4. would be deleted    -   6. Door motion detector detects motion and no RFID is detected        in the zone immediately positioned by the door—Alert Security    -   7. Resident RFID [F] is detected but wide angle motion detector        has not detected movement for over 12 hrs and [M]=1—Alert        Nursing Station        An actively recording camera is STOPPED from further recording        by one of the following Actions:    -   1. The only detectable RFID signal is [F] and conditions (6)        or (7) were not the source triggers    -   2. No RFID detection and no detected movement in the room        for >0.5 hrs    -   3. Manual over-ride from Nursing Station

Bed Bound Movement Therapy

-   -   1. For [N]=1, NUM=number of Staff RFID visits to room per 24 hrs    -   2. For [N]=1, INTV=time period since last exiting of Staff RFID        from room    -   3. If INTV>0.9*[O] then Alert Nursing Station    -   4. If INTV>1.3*[O] then Alarm Nursing Station and Document

Food/Nutrition Tracking

-   -   1. If [M]=1, [N]=0 and [R]=0 then Alarm and document    -   2. If [M]=1, [N]=0 and [R]=1 then Alert and RR=RR+1    -   3. If [M]=1, [N]=0 and RR>3 then Alarm and document

Resident Requires Assistance When Eating

-   -   1. If [M]=1 and [Q]=1 then For Count Staff RFID and Food Tray        RFID in Patient Room during meal times QQ=QQ+1 per day, reset        QQ=0 each night    -   2. If QQ<3 then Alert    -   3. If QQ<2 then Alarm and document        (NOTE: if facility moves residents to another area for        assistance with eating system will miss event)

Social Interaction Tracking

-   -   1. If RFID detected in Occupied Common Areas, then SI=SI+1    -   2. If Resident RFID detected in Room ≠ [F], then SI=SI+1    -   3. If detection of Assigned RFID in [F] and other Resident RFID        in [F], then SI=SI+1    -   4. If detection of Family RFID in [F] while Assigned RFID is in        [F], then SI=SI+1    -   5. At end of day, If SI>4 then [S]=[S]+1    -   6. At end of day, If SI=4 then [S]=[S]    -   7. At end of day, If SI=3 then [S]=[S]−1    -   8. At end of day, If SI=2 then [S]=[S]−2    -   9. At end of day, If SI=1 then [S]=[S]−3 and Alert Nursing        Station    -   10. At end of day, If SI=0 then [S]=[S]−4 and Alarm Nursing        Station and document    -   11. At end of day, If S<5 then Alert Nursing Station    -   12. At end of day, If S<1 then Alarm Nursing Station and        Document

In-Room Therapy Requiring Special Equipment

-   -   1. Skip entire subroutine If [M]=0 or [T]=0    -   2. If Staff RFID and Device RFID are detected in [F], then        TD=TD+1    -   3. If (current military time)>1.2*[T] and TD=0 then Alarm        Nursing Station and document    -   4. If TD=1 then begin TDT=timer    -   5. If TDT>0.9*[T] then Alert Nursing Station    -   6. If TDT>1.2*[T] then Alarm Nursing Station and document    -   7. If TD=2 then TDT=0 and begin timer and TD=0    -   8. Loop back to 1.

RFID Mobile Emergency Call Button

-   -   1. Unique Emergency RFID is detected    -   2. Individual Resident is Identified    -   3. Resident Location is Identified    -   4. Nursing Station is Alarmed    -   5. Location is compared to list of “wired” facility locations    -   6. If location is “wired”, video/audio link is established with        Nursing Station    -   7. If RFID of Staff is present at Nursing Station and “wired”        link existed, then wait 30 seconds for (VERIFY/REJECT) from        Nursing Station before Alarm is transmitted to PDAs. Send Alarm        immediately for VERIFY, no Alarm for REJECT.    -   8. If VERIFY then [U]=[U]+1, reset to [U]=0 at first of month    -   9. If REJECT then [V]=[V]+1, reset to [V]=0 at first of month    -   10. If [U]>1, document to staff “high risk resident”    -   11. If [V]>3, document to staff “resident requires counseling”

Resident Wandering Detection

-   -   1. If [W]=1 and solo Resident RFID (no associated Staff or        Family RFID) is detected approaching or at exit then        -   a. Alert Nursing Station        -   b. Wait 30 seconds for VERIFY/REJECT        -   c. If VERIFY then Establish Video/audio link if location is            “wired”        -   d. If VERIFY then Alarm Staff/Security PDAs        -   e. Document Event        -   f. If 30 seconds elapse with no response from Nursing            Station then d. & e.    -   2. If [X]=1 and solo Resident RFID (no associated Staff or        Family RFID) is detected outside room [F] then        -   a. Alert Nursing Station        -   b. Wait 30 seconds for VERIFY/REJECT        -   c. If VERIFY then Establish Video/audio link if location is            “wired”        -   d. If VERIFY then Alarm Staff PDAs        -   e. Document Event        -   f. If 30 seconds elapse with no response from Nursing            Station then d. & e.    -   3. If Resident RFID is detected in any Facility Area that is        denoted “Restricted” without the presence of Staff RFID then        -   a. Alert Nursing Station        -   b. Wait 30 seconds for VERIFY/REJECT        -   c. If VERIFY then Establish Video/audio link if location is            “wired”        -   d. If VERIFY then Alarm Staff/Security PDAs        -   e. Document Event        -   f. If 30 seconds elapse with no response from Nursing            Station then d. & e.

“Closest Staff Locator”/Shell Method

-   -   For a uniform grid of RFID zones measuring MM by NN and numbered        from left to right, starting in the upper left zone

Shell 0 = X (the present location of the Resident in need) Shell 1 = X −1, X + 1, X + MM, X − MM, X + MM + 1, X + MM − 1, X − MM + 1, X − MM − 1Shell 2 = X − 2, X + 2, X − 2 + MM, X − 2 − MM, X − 2 + 2MM, X − 2 −2MM, X + 2 + MM, X + 2 − MM, X + 2 + 2MM, X + 2 − 2MM, X − 2MM, X −2MM + 1, X − 2MM − 1, X + 2MM, X + 2MM + 1, X + 2MM − 1

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

1. In a computer system that includes a processor and system memory,that maintains stored profiles for a plurality of patients at afacility, and that receives data from networked computers or otherdevices at the facility relating to behavior, activities, care, wellnessor other information for each patient, a method for maintaining thestored profiles for patients at the facility comprising: the computersystem storing an initial profile for each of a plurality of patients ata facility based on at least one of specific personalized informationfor each patient or general information common to more than one patient,the profile for each patient including a limit and/or alarm level foruse in detecting attempted bed exiting by the patient, a first limitand/or alarm level in a first patient profile for use in detectingattempted bed exiting by a first patient differing from a second limitand/or alarm level in a second patient profile for use in detectingattempted bed exiting by a second patient, the profile for each patientoptionally including at least one of a limit for detecting an eventunrelated to attempted bed exiting, an alarm level for use in detectingan actionable event unrelated to attempted bed exiting, a care regimen,or a wellness parameter; the computer system receiving first collecteddata related to bodily movements of the first patient positioned on afirst bed and which are predictive of attempted bed exiting by the firstpatient based on the first patient profile, the data being collectedusing one or more of a sensor, camera or computer positioned at alocation near the first bed on which the first patient is positioned;and the computer system refining the first patient profile for the firstpatient based on the first collected data in order to modify the firstlimit and/or alarm level for use in detecting attempted bed exiting bythe first patient.
 2. A method as defined in claim 1, wherein the firstpatient profile includes both static data and dynamic data relating tobed exiting behavior, wherein refining the first patient profileinvolves altering the dynamic data relating to bed exiting behavior. 3.A method as defined in claim 2, wherein the first patient profile isfurther refined by the computer system automatically altering at leastone of a limit for detecting an event unrelated to attempted bedexiting, an alarm level for detecting an event unrelated to attemptedbed exiting, a treatment regimen, a wellness parameter.
 4. A method asdefined in claim 2, wherein the first patient profile is refined by astaff member manually altering the limit and/or alarm level for use indetecting attempted bed exiting by the patient.
 5. A method as definedin claim 2, wherein the static data remains unmodified.
 6. A method asdefined in claim 1, the first patient profile further including a limitfor detecting an event unrelated to attempted bed exiting, the limitbeing refined in order to more accurately determine occurrence of theevent for the first patient.
 7. A method as defined in claim 6, thefirst patient profile further including an alarm level for detecting anactionable event unrelated to attempted bed exiting, the alarm levelbeing refined in order to more accurately determine occurrence of theactionable event for the first patient.
 8. A method as defined in claim7, the event or actionable event being detected in accordance with arecursively refined profile for the first patient based at least in parton previously collected data.
 9. A method as defined in claim 1, thefirst patient profile including a plurality of limits that indicate aplurality of corresponding body part positions that, when attainedsimultaneously or sequentially, are predictive of bed existing by thefirst patient.
 10. A method as defined in claim 9, wherein refining thefirst patient profile includes modifying the limits based on collecteddata in order to further reduce the risk of unattended bed exiting bythe first patient and/or false positive alerts or alarms relating to thefirst patient.
 11. A method as defined in claim 1, further comprisingcollecting data relating to an event other than attempted bed exiting bythe first patient, the method further comprising staff verifying whetheror not the event is an actionable event, wherein verifying or rejectingthe event as an actionable event forms part of an information feedbackloop that at least partially comprises refining the first patientprofile.
 12. A method as defined in claim 11, wherein the event and/oractionable event relate to at least one of patient wandering intounauthorized zones, patient flight from the facility, patient supportexiting other than bed exiting, patient initiated alert, failure tocomplete a prescribed regimen, or patient injury.
 13. A method asdefined in claim 1, the profile for a patient at the facility beingrefined based on a measured level of social interaction by the patient.14. A method as defined in claim 1, the profile for a patient at thefacility being refined based on a measured level of total ambulation bythe patient over a predetermined period of time.
 15. A method as definedin claim 1, the profile for a patient at the facility being refinedbased on a measured level of total ambulation by the patient over apredetermined period of time in association with a previously definedpersonal ambulation assistive device.
 16. A method as defined in claim1, the profile for a patient at the facility being refined based on ameasured level of denture use by the patient.
 17. A method as defined inclaim 1, the profile for a patient at the facility being refined basedon a measured level of denture cleaning compared to denture cleaningschedules utilized by staff.
 18. A method as defined in claim 1, theprofile for a patient at the facility being refined based completion ofa prescribed patient treatment.
 19. A method as defined in claim 18,wherein the prescribed patient treatment involves an interaction betweenthe patient and at least one of a caregiver or asset.
 20. A method asdefined in claim 1, the profile for a patient at the facility beingrefined based on changes in patient gait.
 21. A method as defined inclaim 1, the profile for a patient at the facility being refined basedon patient breathing that is indicative of a medical condition.
 22. Amethod as defined in claim 1, further comprising storing a performanceprofile for each of a plurality of caregivers and/or visitors at thefacility relating to caregiver and/or visitor performance, collectingdata regarding the locations and/or movements by the caregivers and/orvisitors, and refining caregiver and/or visitor performance profilesbased on the collected data.
 23. A computer-program product comprisingone or more tangible computer-readable media having stored thereoncomputer-executable instructions that, when executed by a processor,cause the computer system to implement the method of claim
 1. 24. In acomputer system that includes a processor and system memory, thatmaintains stored profiles for a plurality of patients at a facility, andthat receives data from networked computers or other devices at thefacility relating to behavior, activities, care, wellness or otherinformation for each patient, a method for maintaining the storedprofiles for patients at the facility comprising: the computer systemstoring an initial profile for each of a plurality of patients at afacility based on at least one of specific personalized information foreach patient or general information common to more than one patient, theprofile for each patient including a limit and/or alarm level for use indetecting attempted bed exiting by the patient, wherein limits and/oralarm levels for use in detecting attempted bed exiting by at least someof the patients at the facility differing from limits and/or alarmlevels for use in detecting attempted bed exiting by at least some otherof the patients at the facility, the profile for each patient optionallyincluding at least one of a limit for detecting an event unrelated toattempted bed exiting, an alarm level for use in detecting anactionable. event unrelated to attempted bed exiting, a care regimen, ora wellness parameter; the computer system receiving collected datarelated to bodily movements for at least some of the patients at thefacility while positioned on respective beds, which movements arepredictive of attempted bed exiting based on stored profiles for thepatients, at least some of which profiles differing based on differencesin attempted bed exiting behaviors as between different patients, thedata being collected using one or more of a sensor, camera or computerpositioned at locations near the beds on which the patients arepositioned; and the computer system refining the profiles for theplurality of patients based on the collected data in order to modifylimits and/or alarm levels for the patients relative to attempted bedexiting, at least some of the patient profiles differing based ondifferences in attempted bed exiting behaviors as between differentpatients.
 25. A method as defined in claim 1, further comprising: thecomputer system receiving second collected data related to bodilymovements of the second patient positioned on a second bed and which arepredictive of attempted bed exiting by the second patient based on thesecond patient profile, the data being collected using one or more of asensor, camera or computer positioned at a location near the first bedon which the first patient is positioned; and the computer systemrefining the second patient profile for the second patient based on thesecond collected data in order to modify the second limit and/or alarmlevel for use in detecting attempted bed exiting by the second patient.26. A method as defined in claim 1, further comprising: the computersystem, when storing an initial profile for at least one of thepatients, further storing information relating to at least one of alimit for detecting an event other than attempted bed exiting, an alarmlevel for use in detecting an actionable event other than attempted bedexiting, a care regimen, or a wellness parameter; the computer systemstoring an initial profile for at least one of a staff member or avisitor at the facility based on at least one of specific personalizedinformation for the staff member and/or visitor, respectively, orgeneral information common to more than one staff member and/or visitor,respectively, the profile for the staff member, if stored by thecomputer system, including a performance parameter for the staff memberand/or the profile for the visitor, if stored by the computer system,including a performance parameter for the visitor; the computer systemreceiving collected data related to at least one of i) a detected eventor an actionable event other than attempted bed exiting by the patient,ii) a care regimen for a patient, iii) a wellness parameter for apatient, (iv) a performance parameter for a staff member, or v) aperformance parameter for a visitor, the data being collected using oneor more of a sensor, camera, or computer positioned within the facilitythat detect and/or analyze data regarding at least one of locationand/or movements by the patient, location and/or movements by staffmembers, assets and/or visitors, physical condition of the patient, oractivities performed on and/or by the patient; and the computer systemrefining the profile for at least one of the patient, staff member orvisitor based on the collected data in order to modify at least one ofthe limit, alarm level, care regimen, or wellness parameter of thepatient, performance parameter for the staff member, or performanceparameter for the visitor.
 27. A method as defined in claim 24, furthercomprising: the computer system, when storing an initial profile for atleast one of the patients, further storing information relating to atleast one of a limit for detecting an event other than attempted bedexiting, an alarm level for use in detecting an actionable event otherthan attempted bed exiting, a care regimen, or a wellness parameter; thecomputer system storing an initial profile for at least one of a staffmember or a visitor at the facility based on at least one of specificpersonalized information for the staff member and/or visitor,respectively, or general information common to more than one staffmember and/or visitor, respectively, the profile for the staff member,if stored by the computer system, including a performance parameter forthe staff member and/or the profile for the visitor, if stored by thecomputer system, including a performance parameter for the visitor; thecomputer system receiving collected data related to at least one of i) adetected event or an actionable event other than attempted bed exitingby the patient, ii) a care regimen for a patient, iii) a wellnessparameter for a patient, (iv) a performance parameter for a staffmember, or v) a performance parameter for a visitor, the data beingcollected using one or more of a sensor, camera, or computer positionedwithin the facility that detect and/or analyze data regarding at leastone of location and/or movements by the patient, location and/ormovements by staff members, assets and/or visitors, physical conditionof the patient, or activities performed on and/or by the patient; andthe computer system refining the profile for at least one of thepatient, staff member or visitor based on the collected data in order tomodify at least one of the limit, alarm level, care regimen, or wellnessparameter of the patient, performance parameter for the staff member, orperformance parameter for the visitor.